Awesome-Omnimodal-Embeddings

Table of Contents

1. Text Embedding

   1.1 Embedding Models

   • Word Vectors
   • BERT-Based Embedding
   • LLM-Based Embedding
   • Instruction-Following Embedding
   • Training Methods
   • Training-Free Methods

   1.2 Embedding Benchmarks

   1.3 Embedding Analysis

   • Interpretability
   • Attack
   • Bias
   • Cross-Lingual Alignment
   • Others

   1.4 Embedding Applications

   • Domain-Specific Embedding
   • Retrieval
   • Reranking
   • Classification & Clustering & STS
   • Sentiment Analysis
   • Discourse Analysis & Topic Modeling
   • LLM Self-Evaluation
   • Regression

2. Code Embedding

   2.1 Models

   2.2 Datasets & Benchmarks

   2.3 Applications

   • Retrieval
   • Reranking
   • Others

3. Vision Embedding

   3.1 Models

   • General Representation Models
   • 3D Representation
   • Video Representation
   • Vision-Language Model
   • Domain-Specific Model

   3.2 Training Methods

   • Contrastive & Self-Supervised Training
   • Disentanglement & Causality & Invariance
   • Robustness, Privacy, Federated & Efficient Training
   • Semi, Weak, Few-Shot Supervision
   • Multimodal Training

   3.3 Datasets & Benchmarks

   3.4 Embedding Analysis

   • Representation Properties & Mechanisms
   • Robustness & Human Alignment
   • Interpretability

   3.5 Embedding Applications

   • Segmentation & Detection
   • Retrieval & Reranking
   • Identification & Surveillance
   • Autonomous Driving
   • Enhancement & Generation & Editing
   • Others

4. Audio Embedding

   4.1 Models

   • Speaker Embedding
   • General Speech Representation
   • Speech Content, Phoneme & Articulatory Representation
   • Emotion, Paralinguistic & Prosody Embedding
   • Multilingual Embedding
   • Multimodal

   4.2 Training Methods

   • Disentanglement & Decoupling
   • Contrastive, Generative & Multi-Objective Learning
   • Distillation, Pruning & Efficiency-Oriented Training
   • Multilingual Training
   • Privacy-Preserving Representation Learning
   • Robustness-Oriented Training
   • Other Methods

   4.3 Embedding Analysis

   • Representation Properties
   • Speaker Characteristics
   • Benchmarking & Evaluating Extractors
   • Interpretability
   • Cross-Domain Generalization

   4.4 Benchmarks & Toolkits

   4.5 Embedding Applications

   • Speaker-Related Application
   • Speech Recognition & Transcription
   • Speech Emotion, Paralinguistic, Health & Cognitive Applications
   • Text-To-Speech
   • Spoofing & Security
   • Others

5. Graph Embedding

   5.1 Node Embedding

   5.2 Graph Embedding

   5.3 Edge Embedding

   5.4 Knowledge Graph Embedding

6. Time Series Embedding

   6.1 Foundation Models

   6.2 Model Architecture & Training Methods

   6.3 Temporal Knowledge Graph

   6.4 Temporal Network

1. Text Embedding

1.1 Embedding Models

Word Vectors

• "Efficient Estimation of Word Representations in Vector Space" [2013-01] [paper]

• "Distributed Representations of Words and Phrases and their Compositionality" [2013-10] [NeurIPS 2013] [paper]

• "GloVe: Global Vectors for Word Representation" [2014-10] [EMNLP 2014] [paper]

• "Axis Tour: Word Tour Determines the Order of Axes in ICA-transformed Embeddings" [2024-01] [EMNLP 2024 Findings] [paper]

• "The Shape of Word Embeddings: Quantifying Non-Isometry with Topological Data Analysis" [2024-04] [EMNLP 2024 Findings] [paper]

• "Statistical Uncertainty in Word Embeddings: GloVe-V" [2024-06] [EMNLP 2024] [paper]

• "Exploring Intra and Inter-language Consistency in Embeddings with ICA" [2024-06] [EMNLP 2024] [paper]

• "GrEmLIn: A Repository of Green Baseline Embeddings for 87 Low-Resource Languages Injected with Multilingual Graph Knowledge" [2024-09] [NAACL 2025 Findings] [paper]

• "Understanding Higher-Order Correlations Among Semantic Components in Embeddings" [2024-09] [EMNLP 2024] [paper]

BERT-Based Embedding

• "BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding" [2018-10] [NAACL 2019] [paper]

• "Cross-lingual Language Model Pretraining" [2019-01] [NeurIPS 2019] [paper]

• "ERNIE: Enhanced Representation through Knowledge Integration" [2019-04] [paper]

• "Unified Language Model Pre-training for Natural Language Understanding and Generation" [2019-05] [NeurIPS 2019] [paper]

• "SpanBERT: Improving Pre-training by Representing and Predicting Spans" [2019-07] [TACL 2020] [paper]

• "RoBERTa: A Robustly Optimized BERT Pretraining Approach" [2019-07] [paper]

• "ERNIE 2.0: A Continual Pre-training Framework for Language Understanding" [2019-07] [AAAI 2020] [paper]

• "StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding" [2019-08] [ICLR 2020] [paper]

• "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks" [2019-08] [EMNLP 2019] [paper]

• "ALBERT: A Lite BERT for Self-supervised Learning of Language Representations" [2019-09] [ICLR 2020] [paper]

• "DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter" [2019-10] [paper]

• "Unsupervised Cross-lingual Representation Learning at Scale" [2019-11] [ACL 2020] [paper]

• "MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers" [2020-02] [NeurIPS 2020] [paper]

• "ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators" [2020-03] [ICLR 2020] [paper]

• "ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT" [2020-04] [SIGIR 2020] [paper]

• "DeBERTa: Decoding-enhanced BERT with Disentangled Attention" [2020-06] [ICLR 2021] [paper]

• "MiniLMv2: Multi-Head Self-Attention Relation Distillation for Compressing Pretrained Transformers" [2020-12] [ACL 2021 Findings] [paper]

• "CANINE: Pre-training an Efficient Tokenization-Free Encoder for Language Representation" [2021-03] [TACL 2022] [paper]

• "SimCSE: Simple Contrastive Learning of Sentence Embeddings" [2021-04] [EMNLP 2021] [paper]

• "Larger-Scale Transformers for Multilingual Masked Language Modeling" [2021-05] [paper]

• "XLM-E: Cross-lingual Language Model Pre-training via ELECTRA" [2021-06] [ACL 2022] [paper]

• "DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing" [2021-11] [ICLR 2023] [paper]

• "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction" [2021-12] [NAACL 2022] [paper]

• "BiTimeBERT: Extending Pre-Trained Language Representations with Bi-Temporal Information" [2022-04] [SIGIR 2023] [paper]

• "SimLM: Pre-training with Representation Bottleneck for Dense Passage Retrieval" [2022-07] [ACL 2023] [paper]

• "Beyond English-Centric Bitexts for Better Multilingual Language Representation Learning" [2022-10] [ACL 2023] [paper]

• "Text Embeddings by Weakly-Supervised Contrastive Pre-training" [2022-12] [paper]

• "Representation Deficiency in Masked Language Modeling" [2023-02] [ICLR 2024] [paper]

• "Dual-Alignment Pre-training for Cross-lingual Sentence Embedding" [2023-05] [ACL 2023] [paper]

• "Glot500: Scaling Multilingual Corpora and Language Models to 500 Languages" [2023-05] [ACL 2023] [paper]

• "Learning Multilingual Sentence Representations with Cross-lingual Consistency Regularization" [2023-06] [EMNLP 2023 Industry] [paper]

• "Towards General Text Embeddings with Multi-stage Contrastive Learning" [2023-08] [paper]

• "Augmenting Transformers with Recursively Composed Multi-grained Representations" [2023-09] [ICLR 2024] [paper]

• "EELBERT: Tiny Models through Dynamic Embeddings" [2023-10] [EMNLP 2023 Industry] [paper]

• "Learning Mutually Informed Representations for Characters and Subwords" [2023-11] [NAACL 2024 Findings] [paper]

• "BERT Has More to Offer: BERT Layers Combination Yields Better Sentence Embeddings" [2023-12] [EMNLP 2023 Findings] [paper]

• "Nomic Embed: Training a Reproducible Long Context Text Embedder" [2024-02] [TMLR 2025] [paper]

• "M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation" [2024-02] [ACL 2024 Findings] [paper]

• "Multilingual E5 Text Embeddings: A Technical Report" [2024-02] [paper]

• "Are ELECTRA’s Sentence Embeddings Beyond Repair? The Case of Semantic Textual Similarity" [2024-02] [EMNLP 2024 Findings] [paper]

• "NextLevelBERT: Masked Language Modeling with Higher-Level Representations for Long Documents" [2024-02] [ACL 2024] [paper]

• "Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models" [2024-05] [paper]

• "Subword Attention and Post-Processing for Rare and Unknown Contextualized Embeddings" [2024-06] [NAACL 2024 Findings] [paper]

• "mGTE: Generalized Long-Context Text Representation and Reranking Models for Multilingual Text Retrieval" [2024-07] [EMNLP 2024 Industry] [paper]

• "MEXMA: Token-level objectives improve sentence representations" [2024-09] [ACL 2025] [paper]

• "Arctic-Embed 2.0: Multilingual Retrieval Without Compromise" [2024-12] [paper]

• "Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference" [2024-12] [ACL 2025] [paper]

• "NeoBERT: A Next-Generation BERT" [2025-02] [TMLR 2025] [paper]

• "Beyond instruction-conditioning, MoTE: Mixture of Task Experts for Multi-task Embedding Models" [2025-07] [ACL 2025 Findings] [paper]

• "mmBERT: A Modern Multilingual Encoder with Annealed Language Learning" [2025-09] [paper]

LLM-Based Embedding

• "Text and Code Embeddings by Contrastive Pre-Training" [2022-01] [paper]

• "SGPT: GPT Sentence Embeddings for Semantic Search" [2022-02] [paper]

• "Scaling Sentence Embeddings with Large Language Models" [2023-07] [EMNLP 2024 Findings] [paper]

• "Nugget: Neural Agglomerative Embeddings of Text" [2023-10] [ICML 2023] [paper]

• "BeLLM: Backward Dependency Enhanced Large Language Model for Sentence Embeddings" [2023-11] [NAACL 2024] [paper]

• "Improving Text Embeddings with Large Language Models" [2024-01] [ACL 2024] [paper]

• "Generative Representational Instruction Tuning" [2024-02] [ICLR 2025] [paper]

• "Gecko: Versatile Text Embeddings Distilled from Large Language Models" [2024-03] [paper]

• "LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders" [2024-04] [paper]

• "NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models" [2024-05] [ICLR 2025] [paper]

• "Llama2Vec: Unsupervised Adaptation of Large Language Models for Dense Retrieval" [2024-08] [ACL 2024] [paper]

• "Making Text Embedders Few-Shot Learners" [2024-09] [ICLR 2025] [paper]

• "Linq-Embed-Mistral Technical Report" [2024-12] [paper]

• "LUSIFER: Language Universal Space Integration for Enhanced Multilingual Embeddings with Large Language Models" [2025-01] [SIGIR 2025] [paper]

• "Enhancing Lexicon-Based Text Embeddings with Large Language Models" [2025-01] [ACL 2025] [paper]

• "Cramming 1568 Tokens into a Single Vector and Back Again: Exploring the Limits of Embedding Space Capacity" [2025-02] [ACL 2025] [paper]

• "Gemini Embedding: Generalizable Embeddings from Gemini" [2025-03] [paper]

• "CSE-SFP: Enabling Unsupervised Sentence Representation Learning via a Single Forward Pass" [2025-05] [SIGIR 2025] [paper]

• "Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models" [2025-06] [paper]

• "LGAI-EMBEDDING-Preview Technical Report" [2025-06] [paper]

• "Learning to Look at the Other Side: A Semantic Probing Study of Word Embeddings in LLMs with Enabled Bidirectional Attention" [2025-07] [ACL 2025] [paper]

• "Training LLMs to be Better Text Embedders through Bidirectional Reconstruction" [2025-09] [EMNLP 2025] [paper]

• "Conan-Embedding-v2: Training an LLM from Scratch for Text Embeddings" [2025-09] [paper]

• "EmbeddingGemma: Powerful and Lightweight Text Representations" [2025-09] [paper]

• "F2LLM Technical Report: Matching SOTA Embedding Performance with 6 Million Open-Source Data" [2025-10] [paper]

Instruction-Following Embedding

• "One Embedder, Any Task: Instruction-Finetuned Text Embeddings" [2022-12] [ACL 2023 Findings] [paper]

• "DATA-CUBE: Data Curriculum for Instruction-based Sentence Representation Learning" [2024-01] [ACL 2024 Findings] [paper]

• "Answer is All You Need: Instruction-following Text Embedding via Answering the Question" [2024-02] [ACL 2024] [paper]

• "Hyper-CL: Conditioning Sentence Representations with Hypernetworks" [2024-03] [ACL 2024] [paper]

• "Promptriever: Instruction-Trained Retrievers Can Be Prompted Like Language Models" [2024-09] [ICLR 2025] [paper]

• "Varying Sentence Representations via Condition-Specified Routers" [2024-11] [EMNLP 2024] [paper]

Training Methods

• "Ranking-Enhanced Unsupervised Sentence Representation Learning" [2022-09] [ACL 2023] [paper]

• "Language Agnostic Multilingual Information Retrieval with Contrastive Learning" [2022-10] [ACL 2023 Findings] [paper]

• "miCSE: Mutual Information Contrastive Learning for Low-shot Sentence Embeddings" [2022-11] [ACL 2023] [paper]

• "Improving Contrastive Learning of Sentence Embeddings from AI Feedback" [2023-05] [ACL 2023 Findings] [paper]

• "StrAE: Autoencoding for Pre-Trained Embeddings using Explicit Structure" [2023-05] [EMNLP 2023] [paper]

• "Alleviating Over-smoothing for Unsupervised Sentence Representation" [2023-05] [ACL 2023] [paper]

• "Distilling Semantic Concept Embeddings from Contrastively Fine-Tuned Language Models" [2023-05] [SIGIR 2023] [paper]

• "SimCSE++: Improving Contrastive Learning for Sentence Embeddings from Two Perspectives" [2023-05] [EMNLP 2023] [paper]

• "Bridging Continuous and Discrete Spaces: Interpretable Sentence Representation Learning via Compositional Operations" [2023-05] [EMNLP 2023] [paper]

• "Contrastive Learning of Sentence Embeddings from Scratch" [2023-05] [EMNLP 2023] [paper]

• "Efficient Document Embeddings via Self-Contrastive Bregman Divergence Learning" [2023-05] [ACL 2023 Findings] [paper]

• "RankCSE: Unsupervised Sentence Representations Learning via Learning to Rank" [2023-05] [ACL 2023] [paper]

• "WhitenedCSE: Whitening-based Contrastive Learning of Sentence Embeddings" [2023-05] [ACL 2023] [paper]

• "On The Inadequacy of Optimizing Alignment and Uniformity in Contrastive Learning of Sentence Representations" [2023-05] [ICLR 2023] [paper]

• "Composition-contrastive Learning for Sentence Embeddings" [2023-07] [ACL 2023] [paper]

• "Robustness-Aware Word Embedding Improves Certified Robustness to Adversarial Word Substitutions" [2023-07] [ACL 2023 Findings] [paper]

• "AoE: Angle-optimized Embeddings for Semantic Textual Similarity" [2023-09] [ACL 2024] [paper]

• "Improving Contrastive Learning of Sentence Embeddings with Focal InfoNCE" [2023-10] [EMNLP 2023 Findings] [paper]

• "HiCL: Hierarchical Contrastive Learning of Unsupervised Sentence Embeddings" [2023-10] [EMNLP 2023 Findings] [paper]

• "Large Language Models can Contrastively Refine their Generation for Better Sentence Representation Learning" [2023-10] [NAACL 2024] [paper]

• "DistillCSE: Distilled Contrastive Learning for Sentence Embeddings" [2023-10] [EMNLP 2023 Findings] [paper]

• "On the Dimensionality of Sentence Embeddings" [2023-10] [EMNLP 2023 Findings] [paper]

• "EMMA-X: An EM-like Multilingual Pre-training Algorithm for Cross-lingual Representation Learning" [2023-10] [NeurIPS 2023] [paper]

• "Non-contrastive sentence representations via self-supervision" [2023-10] [NAACL 2024 Findings] [paper]

• "AdaSent: Efficient Domain-Adapted Sentence Embeddings for Few-Shot Classification" [2023-11] [EMNLP 2023] [paper]

• "Sub-Sentence Encoder: Contrastive Learning of Propositional Semantic Representations" [2023-11] [NAACL 2024] [paper]

• "Text Representation Distillation via Information Bottleneck Principle" [2023-11] [EMNLP 2023] [paper]

• "Sparsity-Preserving Differentially Private Training of Large Embedding Models" [2023-11] [NeurIPS 2023] [paper]

• "RobustEmbed: Robust Sentence Embeddings Using Self-Supervised Contrastive Pre-Training" [2023-12] [EMNLP 2023 Findings] [paper]

• "DocSplit: Simple Contrastive Pretraining for Large Document Embeddings" [2023-12] [EMNLP 2023 Findings] [paper]

• "OssCSE: Overcoming Surface Structure Bias in Contrastive Learning for Unsupervised Sentence Embedding" [2023-12] [EMNLP 2023] [paper]

• "Landmark Embedding: A Chunking-Free Embedding Method For Retrieval Augmented Long-Context Large Language Models" [2024-02] [ACL 2024] [paper]

• "ESE: Espresso Sentence Embeddings" [2024-02] [ICLR 2025] [paper]

• "Towards Better Understanding of Contrastive Sentence Representation Learning: A Unified Paradigm for Gradient" [2024-02] [ACL 2024] [paper]

• "RobustSentEmbed: Robust Sentence Embeddings Using Adversarial Self-Supervised Contrastive Learning" [2024-03] [NAACL 2024 Findings] [paper]

• "Space Decomposition for Sentence Embedding" [2024-06] [ACL 2024 Findings] [paper]

• "Repurposing Language Models into Embedding Models: Finding the Compute-Optimal Recipe" [2024-06] [NeurIPS 2024] [paper]

• "Representation Learning with Conditional Information Flow Maximization" [2024-06] [ACL 2024] [paper]

• "SKICSE: Sentence Knowable Information Prompted by LLMs Improves Contrastive Sentence Embeddings" [2024-06] [NAACL 2024] [paper]

• "Banyan: Improved Representation Learning with Explicit Structure" [2024-07] [ICML 2025] [paper]

• "Matryoshka-Adaptor: Unsupervised and Supervised Tuning for Smaller Embedding Dimensions" [2024-07] [EMNLP 2024] [paper]

• "VAEGPT-Sim: Improving Sentence Representation with Limited Corpus Using Gradually-Denoising VAE" [2024-08] [ACL 2024 Findings] [paper]

• "Enhancing Unsupervised Sentence Embeddings via Knowledge-Driven Data Augmentation and Gaussian-Decayed Contrastive Learning" [2024-09] [ACL 2025] [paper]

• "Contextual Document Embeddings" [2024-10] [ICLR 2025] [paper]

• "Little Giants: Synthesizing High-Quality Embedding Data at Scale" [2024-10] [NAACL 2025] [paper]

• "A Simple Angle-based Approach for Contrastive Learning of Unsupervised Sentence Representation" [2024-11] [EMNLP 2024 Findings] [paper]

• "MAGNET: Augmenting Generative Decoders with Representation Learning and Infilling Capabilities" [2025-01] [ACL 2025] [paper]

• "Better Embeddings with Coupled Adam" [2025-02] [ACL 2025] [paper]

• "Refining Sentence Embedding Model through Ranking Sentences Generation with Large Language Models" [2025-02] [ACL 2025 Findings] [paper]

• "Multi-Sense Embeddings for Language Models and Knowledge Distillation" [2025-04] [ACL 2025 Findings] [paper]

• "Effective post-training embedding compression via temperature control in contrastive training" [2025-04] [ICLR 2025] [paper]

• "Don’t Reinvent the Wheel: Efficient Instruction-Following Text Embedding based on Guided Space Transformation" [2025-05] [ACL 2025] [paper]

• "Adapting General-Purpose Embedding Models to Private Datasets Using Keyword-based Retrieval" [2025-05] [ACL 2025 Findings] [paper]

• "On the Relation Between Fine-Tuning, Topological Properties, and Task Performance in Sense-Enhanced Embeddings" [2025-07] [ACL 2025] [paper]

• "Cheap Character Noise for OCR-Robust Multilingual Embeddings" [2025-07] [ACL 2025 Findings] [paper]

• "Negative Matters: Multi-Granularity Hard-Negative Synthesis and Anchor-Token-Aware Pooling for Enhanced Text Embeddings" [2025-07] [ACL 2025] [paper]

• "Understanding the Influence of Synthetic Data for Text Embedders" [2025-07] [ACL 2025 Findings] [paper]

Training-Free Methods

• "Ditto: A Simple and Efficient Approach to Improve Sentence Embeddings" [2023-05] [EMNLP 2023] [paper]

• "EmbedTextNet: Dimension Reduction with Weighted Reconstruction and Correlation Losses for Efficient Text Embedding" [2023-07] [ACL 2023 Findings] [paper]

• "Repetition Improves Language Model Embeddings" [2024-02] [ICLR 2025] [paper]

• "Meta-Task Prompting Elicits Embeddings from Large Language Models" [2024-02] [ACL 2024] [paper]

• "PromptReps: Prompting Large Language Models to Generate Dense and Sparse Representations for Zero-Shot Document Retrieval" [2024-04] [EMNLP 2024] [paper]

• "Crafting Interpretable Embeddings for Language Neuroscience by Asking LLMs Questions" [2024-05] [NeurIPS 2024] [paper]

• "Semantic Compression for Word and Sentence Embeddings using Discrete Wavelet Transform" [2024-07] [ACL 2024 Findings] [paper]

• "A General Framework for Producing Interpretable Semantic Text Embeddings" [2024-10] [ICLR 2025] [paper]

• "Your Mixture-of-Experts LLM Is Secretly an Embedding Model for Free" [2024-10] [ICLR 2025] [paper]

• "GenEOL: Harnessing the Generative Power of LLMs for Training-Free Sentence Embeddings" [2024-10] [NAACL 2025 Findings] [paper]

• "Length-Induced Embedding Collapse in PLM-based Models" [2024-10] [ACL 2025] [paper]

• "Token Prepending: A Training-Free Approach for Eliciting Better Sentence Embeddings from LLMs" [2024-12] [ACL 2025] [paper]

• "LDIR: Low-Dimensional Dense and Interpretable Text Embeddings with Relative Representations" [2025-05] [ACL 2025 Findings] [paper]

• "Contrastive Prompting Enhances Sentence Embeddings in LLMs through Inference-Time Steering" [2025-05] [ACL 2025] [paper]

1.2 Embedding Benchmarks

• "SciRepEval: A Multi-Format Benchmark for Scientific Document Representations" [2022-11] [EMNLP 2023] [paper]

• "Moving Beyond Downstream Task Accuracy for Information Retrieval Benchmarking" [2023-07] [ACL 2023 Findings] [paper]

• "C-Pack: Packed Resources For General Chinese Embeddings" [2023-09] [SIGIR 2024] [paper]

• "How Well Do Text Embedding Models Understand Syntax?" [2023-11] [EMNLP 2023 Findings] [paper]

• "FollowIR: Evaluating and Teaching Information Retrieval Models to Follow Instructions" [2024-03] [NAACL 2025] [paper]

• "LongEmbed: Extending Embedding Models for Long Context Retrieval" [2024-04] [EMNLP 2024] [paper]

• "Cocktail: A Comprehensive Information Retrieval Benchmark with LLM-Generated Documents Integration" [2024-05] [ACL 2024 Findings] [paper]

• "The Scandinavian Embedding Benchmarks: Comprehensive Assessment of Multilingual and Monolingual Text Embedding" [2024-06] [NeurIPS 2024] [paper]

• "ClimRetrieve: A Benchmarking Dataset for Information Retrieval from Corporate Climate Disclosures" [2024-06] [EMNLP 2024] [paper]

• "The Russian-focused embedders’ exploration: ruMTEB benchmark and Russian embedding model design" [2024-08] [NAACL 2025] [paper]

• "Swan and ArabicMTEB: Dialect-Aware, Arabic-Centric, Cross-Lingual, and Cross-Cultural Embedding Models and Benchmarks" [2024-11] [NAACL 2025 Findings] [paper]

• "ALIGN-SIM: A Task-Free Test Bed for Evaluating and Interpreting Sentence Embeddings through Semantic Similarity Alignment" [2024-11] [EMNLP 2024 Findings] [paper]

• "AIR-Bench: Automated Heterogeneous Information Retrieval Benchmark" [2024-12] [ACL 2025] [paper]

• "MMTEB: Massive Multilingual Text Embedding Benchmark" [2025-02] [ICLR 2025] [paper]

• "IFIR: A Comprehensive Benchmark for Evaluating Instruction-Following in Expert-Domain Information Retrieval" [2025-03] [NAACL 2025] [paper]

• "On Linear Representations and Pretraining Data Frequency in Language Models" [2025-04] [ICLR 2025] [paper]

• "MedEureka: A Medical Domain Benchmark for Multi-Granularity and Multi-Data-Type Embedding-Based Retrieval" [2025-04] [NAACL 2025 Findings] [paper]

• "Optimized Text Embedding Models and Benchmarks for Amharic Passage Retrieval" [2025-05] [ACL 2025 Findings] [paper]

1.3 Embedding Analysis

Interpretability

• "Interpreting Embedding Spaces by Conceptualization" [2022-08] [EMNLP 2023] [paper]

• "Norm of Word Embedding Encodes Information Gain" [2022-12] [EMNLP 2023] [paper]

• "Discovering Universal Geometry in Embeddings with ICA" [2023-05] [EMNLP 2023] [paper]

• "Estimating class separability of text embeddings with persistent homology" [2023-05] [TMLR 2024] [paper]

• "A Method for Studying Semantic Construal in Grammatical Constructions with Interpretable Contextual Embedding Spaces" [2023-07] [ACL 2023] [paper]

• "Demystifying Embedding Spaces using Large Language Models" [2023-10] [ICLR 2024] [paper]

• "The Linear Representation Hypothesis and the Geometry of Large Language Models" [2023-11] [ICML 2024] [paper]

• "Is Probing All You Need? Indicator Tasks as an Alternative to Probing Embedding Spaces" [2023-12] [EMNLP 2023 Findings] [paper]

• "On the Origins of Linear Representations in Large Language Models" [2024-03] [ICML 2024] [paper]

• "Adjusting Interpretable Dimensions in Embedding Space with Human Judgments" [2024-04] [NAACL 2024] [paper]

• "A Text is Worth Several Tokens: Text Embedding from LLMs Secretly Aligns Well with The Key Tokens" [2024-06] [ACL 2025] [paper]

• "Representational Isomorphism and Alignment of Multilingual Large Language Models" [2024-11] [EMNLP 2024 Findings] [paper]

• "Redundancy, Isotropy, and Intrinsic Dimensionality of Prompt-based Text Embeddings" [2025-06] [ACL 2025 Findings] [paper]

Attack

• "Sentence Embedding Leaks More Information than You Expect: Generative Embedding Inversion Attack to Recover the Whole Sentence" [2023-05] [ACL 2023 Findings] [paper]

• "Text Embedding Inversion Security for Multilingual Language Models" [2024-01] [ACL 2024] [paper]

• "WARDEN: Multi-Directional Backdoor Watermarks for Embedding-as-a-Service Copyright Protection" [2024-03] [ACL 2024] [paper]

• "Can’t Hide Behind the API: Stealing Black-Box Commercial Embedding Models" [2024-06] [NAACL 2025 Findings] [paper]

• "Transferable Embedding Inversion Attack: Uncovering Privacy Risks in Text Embeddings without Model Queries" [2024-06] [ACL 2024] [paper]

• "WET: Overcoming Paraphrasing Vulnerabilities in Embeddings-as-a-Service with Linear Transformation Watermarks" [2024-09] [ACL 2025] [paper]

• "An Inversion Attack Against Obfuscated Embedding Matrix in Language Model Inference" [2024-11] [EMNLP 2024] [paper]

• "GuardEmb: Dynamic Watermark for Safeguarding Large Language Model Embedding Service Against Model Stealing Attack" [2024-11] [EMNLP 2024 Findings] [paper]

• "ALGEN: Few-shot Inversion Attacks on Textual Embeddings via Cross-Model Alignment and Generation" [2025-02] [ACL 2025] [paper]

• "Sticking to the Mean: Detecting Sticky Tokens in Text Embedding Models" [2025-07] [ACL 2025] [paper]

Bias

• "Investigating the Frequency Distortion of Word Embeddings and Its Impact on Bias Metrics" [2022-11] [EMNLP 2023 Findings] [paper]

• "Is a Prestigious Job the same as a Prestigious Country? A Case Study on Multilingual Sentence Embeddings and European Countries" [2023-05] [EMNLP 2023 Findings] [paper]

• "Debiasing with Sufficient Projection: A General Theoretical Framework for Vector Representations" [2024-06] [NAACL 2024] [paper]

• "Discovering Biases in Information Retrieval Models Using Relevance Thesaurus as Global Explanation" [2024-10] [EMNLP 2024] [paper]

• "What is in a name? Mitigating Name Bias in Text Embedding Similarity via Anonymization" [2025-02] [ACL 2025 Findings] [paper]

• "PRISM: A Framework for Producing Interpretable Political Bias Embeddings with Political-Aware Cross-Encoder" [2025-05] [ACL 2025] [paper]

Cross-Lingual Alignment

• "Understanding Linearity of Cross-Lingual Word Embedding Mappings" [2020-04] [TMLR 2022] [paper]

• "Linear Cross-Lingual Mapping of Sentence Embeddings" [2023-05] [ACL 2024 Findings] [paper]

• "Hyperpolyglot LLMs: Cross-Lingual Interpretability in Token Embeddings" [2023-11] [EMNLP 2023] [paper]

• "Enhancing Cross-lingual Sentence Embedding for Low-resource Languages with Word Alignment" [2024-04] [NAACL 2024 Findings] [paper]

• "mOthello: When Do Cross-Lingual Representation Alignment and Cross-Lingual Transfer Emerge in Multilingual Models?" [2024-04] [NAACL 2024 Findings] [paper]

• "The Semantic Hub Hypothesis: Language Models Share Semantic Representations Across Languages and Modalities" [2024-11] [ICLR 2025] [paper]

• "Steering into New Embedding Spaces: Analyzing Cross-Lingual Alignment Induced by Model Interventions in Multilingual Language Models" [2025-02] [ACL 2025] [paper]

Others

• "The Trade-off between Universality and Label Efficiency of Representations from Contrastive Learning" [2023-03] [ICLR 2023] [paper]

• "Text Embeddings Reveal (Almost) As Much As Text" [2023-10] [EMNLP 2023] [paper]

• "When is an Embedding Model More Promising than Another?" [2024-06] [NeurIPS 2024] [paper]

• "Semantics or spelling? Probing contextual word embeddings with orthographic noise" [2024-08] [ACL 2024 Findings] [paper]

• "What Should Embeddings Embed? Autoregressive Models Represent Latent Generating Distributions" [2024-06] [TMLR 2025] [paper]

• "Layer by Layer: Uncovering Hidden Representations in Language Models" [2025-02] [ICML 2025] [paper]

• "Embedding-Converter: A Unified Framework for Cross-Model Embedding Transformation" [2025-07] [ACL 2025] [paper]

1.4 Embedding Applications

Domain-Specific Embedding

• "Greenback Bears and Fiscal Hawks: Finance is a Jungle and Text Embeddings Must Adapt" [2024-11] [EMNLP 2024 Industry] [paper]

• "BALI: Enhancing Biomedical Language Representations through Knowledge Graph and Language Model Alignment" [2025-07] [SIGIR 2025] [paper]

Retrieval

• "Dense Passage Retrieval for Open-Domain Question Answering" [2020-04] [EMNLP 2020] [paper]

• "Unsupervised Dense Information Retrieval with Contrastive Learning" [2021-12] [TMLR 2022] [paper]

• "Promptagator: Few-shot Dense Retrieval From 8 Examples" [2022-09] [ICLR 2023] [paper]

• "Precise Zero-Shot Dense Retrieval without Relevance Labels" [2022-12] [ACL 2023] [paper]

• "Evaluating Embedding APIs for Information Retrieval" [2023-05] [ACL 2023 Industry] [paper]

• "Synergistic Interplay between Search and Large Language Models for Information Retrieval" [2023-05] [ACL 2024] [paper]

• "BERM: Training the Balanced and Extractable Representation for Matching to Improve Generalization Ability of Dense Retrieval" [2023-05] [ACL 2023] [paper]

• "Referral Augmentation for Zero-Shot Information Retrieval" [2023-05] [ACL 2024 Findings] [paper]

• "Typo-Robust Representation Learning for Dense Retrieval" [2023-06] [ACL 2023] [paper]

• "Large Language Models for Information Retrieval: A Survey" [2023-08] [arXiv] [paper]

• "Search-Adaptor: Embedding Customization for Information Retrieval" [2023-10] [ACL 2024] [paper]

• "Interpreting Conversational Dense Retrieval by Rewriting-Enhanced Inversion of Session Embedding" [2024-02] [ACL 2024] [paper]

• "Self-Retrieval: End-to-End Information Retrieval with One Large Language Model" [2024-03] [NeurIPS 2024] [paper]

• "Spiral of Silence: How is Large Language Model Killing Information Retrieval?—A Case Study on Open Domain Question Answering" [2024-04] [ACL 2024] [paper]

• "Multivariate Representation Learning for Information Retrieval" [2024-04] [SIGIR 2023] [paper]

• "SetCSE: Set Operations using Contrastive Learning of Sentence Embeddings" [2024-04] [ICLR 2024] [paper]

• "USTAD: Unified Single-model Training Achieving Diverse Scores for Information Retrieval" [2024-05] [ICML 2024] [paper]

• "ContrastiveMix: Overcoming Code-Mixing Dilemma in Cross-Lingual Transfer for Information Retrieval" [2024-06] [NAACL 2024] [paper]

• "A Fresh Take on Stale Embeddings: Improving Dense Retriever Training with Corrector Networks" [2024-09] [ICML 2024] [paper]

• "NUDGE: Lightweight Non-Parametric Fine-Tuning of Embeddings for Retrieval" [2024-09] [ICLR 2025] [paper]

• "Generative Retrieval Meets Multi-Graded Relevance" [2024-09] [NeurIPS 2024] [paper]

• "Link, Synthesize, Retrieve: Universal Document Linking for Zero-Shot Information Retrieval" [2024-10] [EMNLP 2024] [paper]

• "Optimizing Multi-Hop Document Retrieval Through Intermediate Representations" [2025-03] [ACL 2025 Findings] [paper]

• "Search Query Embeddings via User-behavior-driven Contrastive Learning" [2025-04] [NAACL 2025 Industry] [paper]

• "RetrieverGuard: Empowering Information Retrieval to Combat LLM-Generated Misinformation" [2025-04] [NAACL 2025 Findings] [paper]

Reranking

• "Passage Re-ranking with BERT" [2019-01] [arXiv] [paper]

• "Multi-Stage Document Ranking with BERT" [2019-10] [arXiv] [paper]

• "Document Ranking with a Pretrained Sequence-to-Sequence Model" [2020-03] [EMNLP 2020 Findings] [paper]

• "Beyond [CLS] through Ranking by Generation" [2020-10] [EMNLP 2020] [paper]

• "The Expando-Mono-Duo Design Pattern for Text Ranking with Pretrained Sequence-to-Sequence Models" [2021-01] [arXiv] [paper]

• "Rethink Training of BERT Rerankers in Multi-Stage Retrieval Pipeline" [2021-01] [ECIR 2021] [paper]

• "InPars: Unsupervised Dataset Generation for Information Retrieval" [2022-02] [SIGIR 2022] [paper]

• "Improving Passage Retrieval with Zero-Shot Question Generation" [2022-04] [EMNLP 2022] [paper]

• "RankT5: Fine-Tuning T5 for Text Ranking with Ranking Losses" [2022-10] [SIGIR 2023] [paper]

• "ExaRanker: Synthetic Explanations Improve Neural Rankers" [2023-01] [SIGIR 2023] [paper]

• "Is ChatGPT Good at Search? Investigating Large Language Models as Re-Ranking Agents" [2023-04] [EMNLP 2023] [paper]

• "Zero-Shot Listwise Document Reranking with a Large Language Model" [2023-05] [arXiv] [paper]

• "Discrete Prompt Optimization via Constrained Generation for Zero-shot Re-ranker" [2023-05] [ACL 2023 Findings] [paper]

• "Large Language Models are Effective Text Rankers with Pairwise Ranking Prompting" [2023-06] [NAACL 2024 Findings] [paper]

• "RankVicuna: Zero-Shot Listwise Document Reranking with Open-Source Large Language Models" [2023-09] [arXiv] [paper]

• "Fine-Tuning LLaMA for Multi-Stage Text Retrieval" [2023-10] [SIGIR 2024] [paper]

• "A Setwise Approach for Effective and Highly Efficient Zero-shot Ranking with Large Language Models" [2023-10] [SIGIR 2024] [paper]

• "Open-source Large Language Models are Strong Zero-shot Query Likelihood Models for Document Ranking" [2023-10] [EMNLP 2023 Findings] [paper]

• "Beyond Yes and No: Improving Zero-Shot LLM Rankers via Scoring Fine-Grained Relevance Labels" [2023-10] [NAACL 2024] [paper]

• "PaRaDe: Passage Ranking using Demonstrations with LLMs" [2023-10] [EMNLP 2023 Findings] [paper]

• "A Two-Stage Adaptation of Large Language Models for Text Ranking" [2023-11] [ACL 2024 Findings] [paper]

• "RankZephyr: Effective and Robust Zero-Shot Listwise Reranking is a Breeze!" [2023-12] [arXiv] [paper]

• "Zero-Shot Cross-Lingual Reranking with Large Language Models for Low-Resource Languages" [2023-12] [ACL 2024] [paper]

• "Expand, Highlight, Generate: RL-driven Document Generation for Passage Reranking" [2023-12] [EMNLP 2023] [paper]

• "EcoRank: Budget-Constrained Text Re-ranking Using Large Language Models" [2024-02] [ACL 2024 Findings] [paper]

• "ListT5: Listwise Reranking with Fusion-in-Decoder Improves Zero-shot Retrieval" [2024-02] [ACL 2024] [paper]

• "Consolidating Ranking and Relevance Predictions of Large Language Models through Post-Processing" [2024-04] [EMNLP 2024] [paper]

• "AGRaME: Any-Granularity Ranking with Multi-Vector Embeddings" [2024-05] [EMNLP 2024] [paper]

• "Leveraging Passage Embeddings for Efficient Listwise Reranking with Large Language Models" [2024-06] [WWW 2025] [paper]

• "FIRST: Faster Improved Listwise Reranking with Single Token Decoding" [2024-06] [EMNLP 2024] [paper]

• "RankRAG: Unifying Context Ranking with Retrieval-Augmented Generation in LLMs" [2024-07] [NeurIPS 2024] [paper]

• "PRP-Graph: Pairwise Ranking Prompting to LLMs with Graph Aggregation for Effective Text Re-ranking" [2024-08] [ACL 2024] [paper]

• "Few-shot Prompting for Pairwise Ranking: An Effective Non-Parametric Retrieval Model" [2024-09] [EMNLP 2024 Findings] [paper]

• "HyQE: Ranking Contexts with Hypothetical Query Embeddings" [2024-10] [EMNLP 2024 Findings] [paper]

• "Sliding Windows Are Not the End: Exploring Full Ranking with Long-Context Large Language Models" [2024-12] [ACL 2025] [paper]

• "ASRank: Zero-Shot Re-Ranking with Answer Scent for Document Retrieval" [2025-01] [NAACL 2025 Findings] [paper]

• "Gumbel Reranking: Differentiable End-to-End Reranker Optimization" [2025-02] [ACL 2025] [paper]

• "Beyond Prompting: An Efficient Embedding Framework for Open-Domain Question Answering" [2025-03] [ACL 2025] [paper]

• "Shifting from Ranking to Set Selection for Retrieval Augmented Generation" [2025-07] [ACL 2025] [paper]

• "QDER: Query-Specific Document and Entity Representations for Multi-Vector Document Re-Ranking" [2025-07] [SIGIR 2025] [paper]

Classification & Clustering & STS

• "Robust Representation Learning with Reliable Pseudo-labels Generation via Self-Adaptive Optimal Transport for Short Text Clustering" [2023-05] [ACL 2023] [paper]

• "Going Beyond Sentence Embeddings: A Token-Level Matching Algorithm for Calculating Semantic Textual Similarity" [2023-07] [ACL 2023] [paper]

• "Transductive Learning for Textual Few-Shot Classification in API-based Embedding Models" [2023-10] [EMNLP 2023] [paper]

• "Hierarchical Level-Wise News Article Clustering via Multilingual Matryoshka Embeddings" [2025-06] [ACL 2025] [paper]

Sentiment Analysis

• "Label-Aware Hyperbolic Embeddings for Fine-grained Emotion Classification" [2023-06] [ACL 2023] [paper]

• "TATA: Stance Detection via Topic-Agnostic and Topic-Aware Embeddings" [2023-10] [EMNLP 2023] [paper]

• "Chain-of-Thought Embeddings for Stance Detection on Social Media" [2023-10] [EMNLP 2023 Findings] [paper]

• "Unmasking the Hidden Meaning: Bridging Implicit and Explicit Hate Speech Embedding Representations" [2023-12] [EMNLP 2023 Findings] [paper]

Discourse Analysis & Topic Modeling

• "Effective Neural Topic Modeling with Embedding Clustering Regularization" [2023-06] [ICML 2023] [paper]

• "Context-guided Embedding Adaptation for Effective Topic Modeling in Low-Resource Regimes" [2023-12] [NeurIPS 2023] [paper]

• "Matching Varying-Length Texts via Topic-Informed and Decoupled Sentence Embeddings" [2024-06] [NAACL 2024 Findings] [paper]

• "Story Embeddings — Narrative-Focused Representations of Fictional Stories" [2024-11] [EMNLP 2024] [paper]

• "Topic Modeling: Contextual Token Embeddings Are All You Need" [2024-11] [EMNLP 2024 Findings] [paper]

• "Conditional Dichotomy Quantification via Geometric Embedding" [2025-07] [ACL 2025] [paper]

LLM Self-Evaluation

• "Analyzing Transformers in Embedding Space" [2022-09] [ACL 2023] [paper]

• "SelfIE: Self-Interpretation of Large Language Model Embeddings" [2024-03] [ICML 2024] [paper]

• "Embedding Trajectory for Out-of-Distribution Detection in Mathematical Reasoning" [2024-05] [NeurIPS 2024] [paper]

• "Latent Space Chain-of-Embedding Enables Output-free LLM Self-Evaluation" [2024-10] [ICLR 2025] [paper]

• "Embedding and Gradient Say Wrong: A White-Box Method for Hallucination Detection" [2024-11] [EMNLP 2024] [paper]

• "CED: Comparing Embedding Differences for Detecting Out-of-Distribution and Hallucinated Text" [2024-11] [EMNLP 2024 Findings] [paper]

Regression

• "Understanding LLM Embeddings for Regression" [2024-11] [TMLR 2025] [paper]

2. Code Embedding

2.1 Models

• "Learning and Evaluating Contextual Embedding of Source Code" [2019-12] [ICML 2020] [paper]

• "CodeBERT: A Pre-Trained Model for Programming and Natural Languages" [2020-02] [EMNLP 2020 findings] [paper]

• "GraphCodeBERT: Pre-training Code Representations with Data Flow" [2020-09] [ICLR 2021] [paper]

• "Multi-task Learning based Pre-trained Language Model for Code Completion" [2020-12] [ASE 2020] [paper]

• "SynCoBERT: Syntax-Guided Multi-Modal Contrastive Pre-Training for Code Representation" [2021-08] [paper]

• "Towards Learning (Dis)-Similarity of Source Code from Program Contrasts" [2021-10] [ACL 2022] [paper]

• "UniXcoder: Unified Cross-Modal Pre-training for Code Representation" [2022-03] [ACL 2022] [paper]

• "CODE-MVP: Learning to Represent Source Code from Multiple Views with Contrastive Pre-Training" [2022-05] [NAACL 2022 Findings] [paper]

• "Pre-Training Representations of Binary Code Using Contrastive Learning" [2022-10] [TMLR 2025] [paper]

• "Code Representation Pre-training with Complements from Program Executions" [2023-09] [EMNLP 2024 Industry] [paper]

• "Language Agnostic Code Embeddings" [2023-10] [NAACL 2024] [paper]

• "Pass-Tuning: Towards Structure-Aware Parameter-Efficient Tuning for Code Representation Learning" [2023-12] [EMNLP 2023 Findings] [paper]

• "Code Representation Learning At Scale" [2024-02] [ICLR 2024] [paper]

• "GALLa: Graph Aligned Large Language Models for Improved Source Code Understanding" [2024-09] [ACL 2025] [paper]

• "CodeXEmbed: A Generalist Embedding Model Family for Multiligual and Multi-task Code Retrieval" [2024-11] [paper]

• "CodeSSM: Towards State Space Models for Code Understanding" [2025-05] [EMNLP 2025] [paper]

• "Towards A Generalist Code Embedding Model Based On Massive Data Synthesis" [2025-05] [paper]

• "Efficient Code Embeddings from Code Generation Models" [2025-08] [paper]

2.2 Datasets & Benchmarks

• "StaQC: A Systematically Mined Question-Code Dataset from Stack Overflow" [2018-03] [WWW 2018] [paper]

• "Deep Code Search" [2018-05] [ICSE 2018] [paper]

• "Learning to Mine Aligned Code and Natural Language Pairs from Stack Overflow" [2018-05] [MSR 2018] [paper]

• "CodeSearchNet Challenge: Evaluating the State of Semantic Code Search" [2019-09] [paper]

• "CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation" [2021-02] [NeurIPS 2021 Datasets and Benchmarks] [paper]

• "CoSQA: 20,000+ Web Queries for Code Search and Question Answering" [2021-05] [ACL 2021] [paper]

• "ProCQA: A Large-scale Community-based Programming Question Answering Dataset for Code Search" [2024-03] [LREC 2024] [paper]

• "CodeRAG-Bench: Can Retrieval Augment Code Generation?" [2024-06] [NAACL 2025 Findings] [paper]

• "CoIR: A Comprehensive Benchmark for Code Information Retrieval Models" [2024-07] [ACL 2025] [paper]

• "What can Large Language Models Capture about Code Functional Equivalence?" [2024-08] [NAACL 2025 Findings] [paper]

• "CmdCaliper: A Semantic-Aware Command-Line Embedding Model and Dataset for Security Research" [2024-11] [EMNLP 2024] [paper]

• "CoRNStack: High-Quality Contrastive Data for Better Code Retrieval and Reranking" [2024-12] [ICLR 2025] [paper]

2.3 Applications

Retrieval

• "Self-Supervised Contrastive Learning for Code Retrieval and Summarization via Semantic-Preserving Transformations" [2020-09] [SIGIR 2021] [paper]

• "REINFOREST: Reinforcing Semantic Code Similarity for Cross-Lingual Code Search Models" [2023-05] [paper]

• "Rewriting the Code: A Simple Method for Large Language Model Augmented Code Search" [2024-01] [ACL 2024] [paper]

• "Revisiting Code Similarity Evaluation with Abstract Syntax Tree Edit Distance" [2024-04] [ACL 2024 short] [paper]

• "You Augment Me: Exploring ChatGPT-based Data Augmentation for Semantic Code Search" [2024-08] [paper]

• "Instructive Code Retriever: Learn from Large Language Model's Feedback for Code Intelligence Tasks" [2024-10] [ASE 2024] [paper]

• "Optimizing Code Retrieval: High-Quality and Scalable Dataset Annotation through Large Language Models" [2024-11] [EMNLP 2024] [paper]

• "Enhancing Learning-Based Binary Code Similarity Detection Model through Adversarial Training with Multiple Function Variants" [2024-11] [EMNLP 2024 Findings] [paper]

• "OASIS: Order-Augmented Strategy for Improved Code Search" [2025-03] [ACL 2025] [paper]

• "Zero-Shot Cross-Domain Code Search without Fine-Tuning" [2025-04] [paper]

• "CoRet: Improved Retriever for Code Editing" [2025-05] [ACL 2025] [paper]

• "Beyond the Surface: A Solution-Aware Retrieval Model for Competition-level Code Generation" [2025-09] [EMNLP 2025 Findings] [paper]

• "Beyond Function-Level Search: Repository-Aware Dual-Encoder Code Retrieval with Adversarial Verification" [2025-10] [EMNLP 2025 Findings] [paper]

Reranking

• "Fault-Aware Neural Code Rankers" [2022-06] [NeurIPS 2022] [paper]

• "Coder Reviewer Reranking for Code Generation" [2022-11] [ICML 2023] [paper]

• "LEVER: Learning to Verify Language-to-Code Generation with Execution" [2023-02] [ICML 2023] [paper]

• "Functional Overlap Reranking for Neural Code Generation" [2023-10] [ACL 2024 Findings] [paper]

• "Top Pass: Improve Code Generation by Pass@k-Maximized Code Ranking" [2024-08] [paper]

• "Sifting through the Chaff: On Utilizing Execution Feedback for Ranking the Generated Code Candidates" [2024-08] [ASE 2024] [paper]

• "B4: Towards Optimal Assessment of Plausible Code Solutions with Plausible Tests" [2024-09] [ASE 2024] [paper]

Others

• "Coding-PTMs: How to Find Optimal Code Pre-trained Models for Code Embedding in Vulnerability Detection?" [2024-08] [ASE 2024] [paper]

• "Learning Cross-Architecture Instruction Embeddings for Binary Code Analysis in Low-Resource Architectures" [2024-08] [NAACL 2024 Findings] [paper]

• "CLeVeR: Multi-modal Contrastive Learning for Vulnerability Code Representation" [2025-07] [ACL 2025 Findings] [paper]

3. Vision Embedding

3.1 Models

General Representation Models

• "Diffusion Based Representation Learning" [2021-05] [ICML 2023] [paper]

• "Simplicial Embeddings in Self-Supervised Learning and Downstream Classification" [2022-04] [ICLR 2023] [paper]

• "Minimalistic Unsupervised Representation Learning with the Sparse Manifold Transform" [2022-09] [ICLR 2023] [paper]

• "OPERA: Omni-Supervised Representation Learning with Hierarchical Supervisions" [2022-10] [ICCV 2023] [paper]

• "Spatio-Temporal Crop Aggregation for Video Representation Learning" [2022-11] [ICCV 2023] [paper]

• "Semantics-Consistent Feature Search for Self-Supervised Visual Representation Learning" [2022-12] [ICCV 2023] [paper]

• "STAIR: Learning Sparse Text and Image Representation in Grounded Tokens" [2023-01] [EMNLP 2023] [paper]

• "Image-text embedding learning via visual and textual semantic reasoning" [2023-01] [TPAMI 2023] [paper]

• "3D Neural Embedding Likelihood: Probabilistic Inverse Graphics for Robust 6D Pose Estimation" [2023-02] [ICCV 2023] [paper]

• "Embedding Fourier for Ultra-High-Definition Low-Light Image Enhancement" [2023-02] [ICLR 2023] [paper]

• "ELITE: Encoding Visual Concepts into Textual Embeddings for Customized Text-to-Image Generation" [2023-02] [ICCV 2023] [paper]

• "Layer Grafted Pre-training: Bridging Contrastive Learning And Masked Image Modeling For Label-Efficient Representations" [2023-02] [ICLR 2023] [paper]

• "NAISR: A 3D Neural Additive Model for Interpretable Shape Representation" [2023-03] [ICLR 2024] [paper]

• "Open-vocabulary Panoptic Segmentation with Embedding Modulation" [2023-03] [ICCV 2023] [paper]

• "Rotation and Translation Invariant Representation Learning with Implicit Neural Representations" [2023-04] [ICML 2023] [paper]

• "ManagerTower: Aggregating the Insights of Uni-Modal Experts for Vision-Language Representation Learning" [2023-05] [ACL 2023] [paper]

• "Isometric Quotient Variational Auto-Encoders for Structure-Preserving Representation Learning" [2023-05] [NeurIPS 2023] [paper]

• "ADDP: Learning General Representations for Image Recognition and Generation with Alternating Denoising Diffusion Process" [2023-06] [ICLR 2024] [paper]

• "MOFI: Learning Image Representations from Noisy Entity Annotated Images" [2023-06] [ICLR 2024] [paper]

• "MOCA: Self-supervised Representation Learning by Predicting Masked Online Codebook Assignments" [2023-07] [TMLR 2024] [paper]

• "Conditional Cross Attention Network for Multi-Space Embedding without Entanglement in Only a SINGLE Network" [2023-07] [ICCV 2023] [paper]

• "SimFIR: A Simple Framework for Fisheye Image Rectification with Self-supervised Representation Learning" [2023-08] [ICCV 2023] [paper]

• "Boosting Semantic Segmentation from the Perspective of Explicit Class Embeddings" [2023-08] [ICCV 2023] [paper]

• "Dynamics-inspired Neuromorphic Visual Representation Learning" [2023-08] [ICML 2023] [paper]

• "RevColV2: Exploring Disentangled Representations in Masked Image Modeling" [2023-09] [NeurIPS 2023] [paper]

• "URLOST: Unsupervised Representation Learning without Stationarity or Topology" [2023-10] [ICLR 2025] [paper]

• "DyST: Towards Dynamic Neural Scene Representations on Real-World Videos" [2023-10] [ICLR 2024] [paper]

• "E2PNet: Event to Point Cloud Registration with Spatio-Temporal Representation Learning" [2023-10] [NeurIPS 2023] [paper]

• "Florence-2: Advancing a Unified Representation for a Variety of Vision Tasks" [2023-11] [CVPR 2024] [paper]

• "VIT-LENS: Towards Omni-modal Representations" [2023-11] [CVPR 2024] [paper]

• "Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model" [2024-01] [ICML 2024] [paper]

• "Unified Generation, Reconstruction, and Representation: Generalized Diffusion with Adaptive Latent Encoding-Decoding" [2024-02] [ICML 2024] [paper]

• "Revisiting Feature Prediction for Learning Visual Representations from Video" [2024-02] [TMLR 2024] [paper]

• "Tripod: Three Complementary Inductive Biases for Disentangled Representation Learning" [2024-04] [ICML 2024] [paper]

• "Diffusion Bridge AutoEncoders for Unsupervised Representation Learning" [2024-05] [ICLR 2025] [paper]

• "Harmony: A Joint Self-Supervised and Weakly-Supervised Framework for Learning General Purpose Visual Representations" [2024-05] [TMLR 2025] [paper]

• "MSPE: Multi-Scale Patch Embedding Prompts Vision Transformers to Any Resolution" [2024-05] [NeurIPS 2024] [paper]

• "Coarse-To-Fine Tensor Trains for Compact Visual Representations" [2024-06] [ICML 2024] [paper]

• "Learning 1D Causal Visual Representation with De-focus Attention Networks" [2024-06] [NeurIPS 2024] [paper]

• "Learning Color Equivariant Representations" [2024-06] [ICLR 2025] [paper]

• "SuperSVG: Superpixel-based Scalable Vector Graphics Synthesis" [2024-06] [CVPR 2024] [paper]

• "Autoencoding Conditional Neural Processes for Representation Learning" [2024-08] [ICML 2024] [paper]

• "Structuring Representation Geometry with Rotationally Equivariant Contrastive Learning" [2024-08] [ICLR 2024] [paper]

• "Denoising Autoregressive Representation Learning" [2024-09] [ICML 2024] [paper]

• "BiGR: Harnessing Binary Latent Codes for Image Generation and Improved Visual Representation Capabilities" [2024-10] [ICLR 2025] [paper]

• "Pretrained Reversible Generation as Unsupervised Visual Representation Learning" [2024-11] [ICCV 2025] [paper]

• "Beyond Matryoshka: Revisiting Sparse Coding for Adaptive Representation" [2025-03] [ICML 2025] [paper]

• "Spectral State Space Model for Rotation-Invariant Visual Representation Learning" [2025-03] [CVPR 2025] [paper]

• "End-to-End Implicit Neural Representations for Classification" [2025-03] [CVPR 2025] [paper]

• "MergeVQ: A Unified Framework for Visual Generation and Representation with Disentangled Token Merging and Quantization" [2025-03] [CVPR 2025] [paper]

• "Scaling Language-Free Visual Representation Learning" [2025-04] [ICCV 2025] [paper]

• "CTRL-O: Language-Controllable Object-Centric Visual Representation Learning" [2025-03] [CVPR 2025] [paper]

• "Breaking the Modality Barrier: Universal Embedding Learning with Multimodal LLMs" [2025-04] [ACM MM 2025] [paper]

• "PIN: Prolate Spheroidal Wave Function-based Implicit Neural Representations" [2025-05] [ICLR 2025] [paper]

• "GECO: Geometrically Consistent Embedding with Lightspeed Inference" [2025-08] [ICCV 2025] [paper]

• "Efficient Object-Centric Representation Learning using Masked Generative Modeling" [2025-09] [TMLR 2025] [paper]

3D Representation

• "Implicit Autoencoder for Point-Cloud Self-Supervised Representation Learning" [2022-01] [ICCV 2023] [paper]

• "Autoencoders as Cross-Modal Teachers: Can Pretrained 2D Image Transformers Help 3D Representation Learning?" [2022-12] [ICLR 2023] [paper]

• "Contrast with Reconstruct: Contrastive 3D Representation Learning Guided by Generative Pretraining" [2023-02] [ICML 2023] [paper]

• "Clustering based Point Cloud Representation Learning for 3D Analysis" [2023-07] [ICCV 2023] [paper]

• "LinNet: Linear Network for Efficient Point Cloud Representation Learning" [2024-02] [NeurIPS 2024] [paper]

• "Unsupervised 3D Scene Representation Learning via Movable Object Inference" [2024-03] [TMLR 2024] [paper]

• "NeRM: Learning Neural Representations for High-Framerate Human Motion Synthesis" [2024-05] [ICLR 2024] [paper]

• "Neural Pose Representation Learning for Generating and Transferring Non-Rigid Object Poses" [2024-06] [NeurIPS 2024] [paper]

• "Uni3D: Exploring Unified 3D Representation at Scale" [2024-07] [ICLR 2024] [paper]

• "Positional Prompt Tuning for Efficient 3D Representation Learning" [2024-08] [ACM MM 2025] [paper]

• "LaGeM: A Large Geometry Model for 3D Representation Learning and Diffusion" [2024-10] [ICLR 2025] [paper]

• "SE(3) Equivariant Ray Embeddings for Implicit Multi-View Depth Estimation" [2024-11] [NeurIPS 2024] [paper]

• "SEGS-SLAM: Structure-enhanced 3D Gaussian Splatting SLAM with Appearance Embedding" [2025-01] [ICCV 2025] [paper]

• "UniMamba: Unified Spatial-Channel Representation Learning with Group-Efficient Mamba for LiDAR-based 3D Object Detection" [2025-03] [CVPR 2025] [paper]

• "Retri3D: 3D Neural Graphics Representation Retrieval" [2025-05] [ICLR 2025] [paper]

• "StruMamba3D: Exploring Structural Mamba for Self-supervised Point Cloud Representation Learning" [2025-06] [ICCV 2025] [paper]

• "A Neural Representation Framework with LLM-Driven Spatial Reasoning for Open-Vocabulary 3D Visual Grounding" [2025-07] [ACM MM 2025] [paper]

• "SPHERE: Semantic-PHysical Engaged REpresentation for 3D Semantic Scene Completion" [2025-09] [ACM MM 2025] [paper]

• "Unifi3D: A Study on 3D Representations for Generation and Reconstruction in a Common Framework" [2025-09] [TMLR 2025] [paper]

Video Representation

• "Entropy-driven Unsupervised Keypoint Representation Learning in Videos" [2022-09] [ICML 2023] [paper]

• "Progressive Fourier Neural Representation for Sequential Video Compilation" [2023-06] [ICLR 2024] [paper]

• "Hierarchical Spatio-Temporal Representation Learning for Gait Recognition" [2023-07] [ICCV 2023] [paper]

• "Is Overfitting Necessary for Implicit Video Representation?" [2023-08] [ICML 2023] [paper]

• "Video-LLaVA: Learning United Visual Representation by Alignment Before Projection" [2023-11] [EMNLP 2024] [paper]

• "Multi-view Masked Contrastive Representation Learning for Endoscopic Video Analysis" [2024-03] [NeurIPS 2024] [paper]

• "MaskCLR: Attention-Guided Contrastive Learning for Robust Action Representation Learning" [2024-03] [CVPR 2024] [paper]

• "Combining Frame and GOP Embeddings for Neural Video Representation" [2024-03] [CVPR 2024] [paper]

• "ARVideo: Autoregressive Pretraining for Self-Supervised Video Representation Learning" [2024-05] [TMLR 2025] [paper]

• "Visual Representation Learning with Stochastic Frame Prediction" [2024-06] [ICML 2024] [paper]

• "VEDIT: Latent Prediction Architecture For Procedural Video Representation Learning" [2024-10] [ICLR 2025] [paper]

• "SEAL: SEmantic Attention Learning for Long Video Representation" [2024-12] [CVPR 2025] [paper]

• "REGEN: Learning Compact Video Embedding with (Re-)Generative Decoder" [2025-03] [ICCV 2025] [paper]

• "Bootstrap Your Own Views: Masked Ego-Exo Modeling for Fine-grained View-invariant Video Representations" [2025-03] [CVPR 2025] [paper]

• "LV-MAE: Learning Long Video Representations through Masked-Embedding Autoencoders" [2025-04] [ICCV 2025] [paper]

Vision-Language Model

• "Universal Vision-Language Dense Retrieval: Learning A Unified Representation Space for Multi-Modal Retrieval" [2022-09] [ICLR 2023] [paper]

• "Incorporating Structured Representations into Pretrained Vision & Language Models Using Scene Graphs" [2023-05] [EMNLP 2023] [paper]

• "Improved Probabilistic Image-Text Representations" [2023-05] [ICLR 2024] [paper]

• "BLIP-Diffusion: Pre-trained Subject Representation for Controllable Text-to-Image Generation and Editing" [2023-05] [NeurIPS 2023] [paper]

• "Weakly Supervised Vision-and-Language Pre-training with Relative Representations" [2023-05] [ACL 2023] [paper]

• "Learning Mask-aware CLIP Representations for Zero-Shot Segmentation" [2023-09] [NeurIPS 2023] [paper]

• "Achieving Cross Modal Generalization with Multimodal Unified Representation" [2023-10] [NeurIPS 2023] [paper]

• "G2D: From Global to Dense Radiography Representation Learning via Vision-Language Pre-training" [2023-12] [NeurIPS 2024] [paper]

• "PolCLIP: A Unified Image-Text Word Sense Disambiguation Model via Generating Multimodal Complementary Representations" [2024-01] [ACL 2024] [paper]

• "Robust CLIP: Unsupervised Adversarial Fine-Tuning of Vision Embeddings for Robust Large Vision-Language Models" [2024-02] [ICML 2024] [paper]

• "Infrared and Visible Image Fusion with Language-Driven Loss in CLIP Embedding Space" [2024-02] [ACM MM 2025] [paper]

• "CLIPLoss and Norm-Based Data Selection Methods for Multimodal Contrastive Learning" [2024-02] [NeurIPS 2024] [paper]

• "Multilingual Diversity Improves Vision-Language Representations" [2024-02] [NeurIPS 2024] [paper]

• "Demonstrating and Reducing Shortcuts in Vision-Language Representation Learning" [2024-02] [TMLR 2024] [paper]

• "If CLIP Could Talk: Understanding Vision-Language Model Representations Through Their Preferred Concept Descriptions" [2024-03] [EMNLP 2024] [paper]

• "Cascade-CLIP: Cascaded Vision-Language Embeddings Alignment for Zero-Shot Semantic Segmentation" [2024-06] [ICML 2024] [paper]

• "OLIVE: Object Level In-Context Visual Embeddings" [2024-06] [ACL 2024] [paper]

• "VISTA: Visualized Text Embedding For Universal Multi-Modal Retrieval" [2024-06] [ACL 2024] [paper]

• "RWKV-CLIP: A Robust Vision-Language Representation Learner" [2024-06] [EMNLP 2024] [paper]

• "MATE: Meet At The Embedding - Connecting Images with Long Texts" [2024-06] [EMNLP 2024 Findings] [paper]

• "VLM2Vec: Training Vision-Language Models for Massive Multimodal Embedding Tasks" [2024-10] [ICLR 2025] [paper]

• "Interfacing Foundation Models' Embeddings" [2024-10] [NeurIPS 2024] [paper]

• "MIRe: Enhancing Multimodal Queries Representation via Fusion-Free Modality Interaction for Multimodal Retrieval" [2024-11] [ACL 2025 Findings] [paper]

• "Verbalized Representation Learning for Interpretable Few-Shot Generalization" [2024-11] [ICCV 2025] [paper]

• "Beyond Logit Lens: Contextual Embeddings for Robust Hallucination Detection & Grounding in VLMs" [2024-11] [NAACL 2025] [paper]

• "End-to-end Training for Text-to-Image Synthesis using Dual-Text Embeddings" [2025-02] [TMLR 2025] [paper]

• "mmE5: Improving Multimodal Multilingual Embeddings via High-quality Synthetic Data" [2025-02] [ACL 2025 Findings] [paper]

• "CalliReader: Contextualizing Chinese Calligraphy via an Embedding-Aligned Vision-Language Model" [2025-03] [ICCV 2025] [paper]

• "LangBridge: Interpreting Image as a Combination of Language Embeddings" [2025-03] [ICCV 2025] [paper]

• "Not Only Text: Exploring Compositionality of Visual Representations in Vision-Language Models" [2025-03] [CVPR 2025] [paper]

• "BASIC: Boosting Visual Alignment with Intrinsic Refined Embeddings in Multimodal Large Language Models" [2025-08] [ICCV 2025] [paper]

• "ABC: Achieving Better Control of Visual Embeddings using VLLMs" [2025-09] [TMLR 2025] [paper]

Domain-Specific Model

• "Scale-MAE: A Scale-Aware Masked Autoencoder for Multiscale Geospatial Representation Learning" [2022-12] [ICCV 2023] [paper]

• "Parametric Depth Based Feature Representation Learning for Object Detection and Segmentation in Bird's-Eye View" [2023-07] [ICCV 2023] [paper]

• "GEDepth: Ground Embedding for Monocular Depth Estimation" [2023-09] [ICCV 2023] [paper]

• "Rethinking Self-Supervised Visual Representation Learning in Pre-training for 3D Human Pose and Shape Estimation" [2023-09] [ICLR 2023] [paper]

• "Unsupervised Learning of Object-Centric Embeddings for Cell Instance Segmentation in Microscopy Images" [2023-10] [ICCV 2023] [paper]

• "Improving Representation Learning for Histopathologic Images with Cluster Constraints" [2023-10] [ICCV 2023] [paper]

• "Semantic-aware Representation Learning for Homography Estimation" [2024-03] [ACM MM 2024] [paper]

• "Learned Trajectory Embedding for Subspace Clustering" [2024-03] [CVPR 2024] [paper]

• "Multi-Scale Representations by Varying Window Attention for Semantic Segmentation" [2024-04] [ICLR 2024] [paper]

• "2M-AF: A Strong Multi-Modality Framework For Human Action Quality Assessment with Self-supervised Representation Learning" [2024-04] [ACM MM 2024] [paper]

• "Masked Face Recognition with Generative-to-Discriminative Representations" [2024-05] [ICML 2024] [paper]

• "MemeCLIP: Leveraging CLIP Representations for Multimodal Meme Classification" [2024-06] [EMNLP 2024] [paper]

• "DFormer: Rethinking RGBD Representation Learning for Semantic Segmentation" [2024-06] [ICLR 2024] [paper]

• "Self-Supervised Visual Representation Learning for Medical Image Analysis: A Comprehensive Survey" [2024-07] [TMLR 2024] [paper]

• "Learning Uniformly Distributed Embedding Clusters of Stylistic Skills for Physically Simulated Characters" [2024-11] [ACM MM 2025] [paper]

• "2DMamba: Efficient State Space Model for Image Representation with Applications on Giga-Pixel Whole Slide Image Classification" [2024-12] [CVPR 2025] [paper]

• "Any2AnyTryon: Leveraging Adaptive Position Embeddings for Versatile Virtual Clothing Tasks" [2025-01] [ICCV 2025] [paper]

• "Contextual Gesture: Co-Speech Gesture Video Generation through Context-aware Gesture Representation" [2025-02] [ACM MM 2025] [paper]

• "Modeling Fine-Grained Hand-Object Dynamics for Egocentric Video Representation Learning" [2025-03] [ICLR 2025] [paper]

• "Parameter-Efficient Adaptation of Geospatial Foundation Models through Embedding Deflection" [2025-03] [ICCV 2025] [paper]

• "EditCLIP: Representation Learning for Image Editing" [2025-03] [ICCV 2025] [paper]

• "Easy-editable Image Vectorization with Multi-layer Multi-scale Distributed Visual Feature Embedding" [2025-03] [CVPR 2025] [paper]

• "MEDTalk: Multimodal Controlled 3D Facial Animation with Dynamic Emotions by Disentangled Embedding" [2025-07] [ACM MM 2025] [paper]

• "BrainFLORA: Uncovering Brain Concept Representation via Multimodal Neural Embeddings" [2025-07] [ACM MM 2025] [paper]

• "HAMLET-FFD: Hierarchical Adaptive Multi-modal Learning Embeddings Transformation for Face Forgery Detection" [2025-07] [ACM MM 2025] [paper]

• "Capturing More: Learning Multi-Domain Representations for Robust Online Handwriting Verification" [2025-08] [ACM MM 2025] [paper]

3.2 Training Methods

Contrastive & Self-Supervised Training

• "SemPPL: Predicting Pseudo-Labels for Better Contrastive Representations" [2023-01] [ICLR 2023] [paper]

• "RoPAWS: Robust Semi-supervised Representation Learning from Uncurated Data" [2023-02] [ICLR 2023] [paper]

• "Adaptive Similarity Bootstrapping for Self-Distillation Based Representation Learning" [2023-03] [ICCV 2023] [paper]

• "Soft Neighbors are Positive Supporters in Contrastive Visual Representation Learning" [2023-03] [ICLR 2023] [paper]

• "Connecting Multi-modal Contrastive Representations" [2023-05] [NeurIPS 2023] [paper]

• "CSP: Self-Supervised Contrastive Spatial Pre-Training for Geospatial-Visual Representations" [2023-05] [ICML 2023] [paper]

• "Disambiguated Attention Embedding for Multi-Instance Partial-Label Learning" [2023-05] [NeurIPS 2023] [paper]

• "Self-Supervised Set Representation Learning for Unsupervised Meta-Learning" [2023-05] [ICLR 2023] [paper]

• "Learning Fine-grained View-Invariant Representations from Unpaired Ego-Exo Videos via Temporal Alignment" [2023-06] [NeurIPS 2023] [paper]

• "Patch-Level Contrasting without Patch Correspondence for Accurate and Dense Contrastive Representation Learning" [2023-06] [ICLR 2023] [paper]

• "Semantic Positive Pairs for Enhancing Visual Representation Learning of Instance Discrimination Methods" [2023-06] [TMLR 2024] [paper]

• "Hallucination Improves the Performance of Unsupervised Visual Representation Learning" [2023-07] [ICCV 2023] [paper]

• "StableRep: Synthetic Images from Text-to-Image Models Make Strong Visual Representation Learners" [2023-07] [NeurIPS 2023] [paper]

• "ArCL: Enhancing Contrastive Learning with Augmentation-Robust Representations" [2023-07] [ICLR 2023] [paper]

• "Self-Weighted Contrastive Learning among Multiple Views for Mitigating Representation Degeneration" [2023-07] [NeurIPS 2023] [paper]

• "Motion-Guided Masking for Spatiotemporal Representation Learning" [2023-08] [ICCV 2023] [paper]

• "Time to augment self-supervised visual representation learning" [2023-08] [ICLR 2023] [paper]

• "Efficient Self-supervised Learning with Contextualized Target Representations for Vision, Speech and Language" [2023-08] [ICML 2023] [paper]

• "Probabilistic Self-supervised Representation Learning via Scoring Rules Minimization" [2023-09] [ICLR 2024] [paper]

• "Multi-Object Representation Learning via Feature Connectivity and Object-Centric Regularization" [2023-09] [NeurIPS 2023] [paper]

• "Mosaic Representation Learning for Self-supervised Visual Pre-training" [2023-09] [ICLR 2023] [paper]

• "Sub-token ViT Embedding via Stochastic Resonance Transformers" [2023-10] [ICML 2024] [paper]

• "Representation Learning via Consistent Assignment of Views over Random Partitions" [2023-10] [NeurIPS 2023] [paper]

• "Combating Representation Learning Disparity with Geometric Harmonization" [2023-10] [NeurIPS 2023] [paper]

• "Embedding Space Interpolation Beyond Mini-Batch, Beyond Pairs and Beyond Examples" [2023-10] [NeurIPS 2023] [paper]

• "Progressively Compressed Auto-Encoder for Self-supervised Representation Learning" [2023-10] [ICLR 2023] [paper]

• "Rejuvenating image-GPT as Strong Visual Representation Learners" [2023-12] [ICML 2024] [paper]

• "ProFeAT: Projected Feature Adversarial Training for Self-Supervised Learning of Robust Representations" [2024-01] [TMLR 2024] [paper]

• "Separating common from salient patterns with Contrastive Representation Learning" [2024-02] [ICLR 2024] [paper]

• "Connecting Joint-Embedding Predictive Architecture with Contrastive Self-supervised Learning" [2024-02] [NeurIPS 2024] [paper]

• "No Train, all Gain: Self-Supervised Gradients Improve Deep Frozen Representations" [2024-02] [NeurIPS 2024] [paper]

• "Easy Regional Contrastive Learning of Expressive Fashion Representations" [2024-02] [NeurIPS 2024] [paper]

• "LeOCLR: Leveraging Original Images for Contrastive Learning of Visual Representations" [2024-03] [TMLR 2024] [paper]

• "Targeted Representation Alignment for Open-World Semi-Supervised Learning" [2024-03] [CVPR 2024] [paper]

• "D3still: Decoupled Differential Distillation for Asymmetric Image Retrieval" [2024-03] [CVPR 2024] [paper]

• "Self-supervised Representation Learning from Random Data Projectors" [2024-05] [ICLR 2024] [paper]

• "Contrasting Multiple Representations with the Multi-Marginal Matching Gap" [2024-05] [ICML 2024] [paper]

• "On the Role of Discrete Tokenization in Visual Representation Learning" [2024-07] [ICLR 2024] [paper]

• "T-MARS: Improving Visual Representations by Circumventing Text Feature Learning" [2024-08] [ICLR 2024] [paper]

• "AUC-CL: A Batchsize-Robust Framework for Self-Supervised Contrastive Representation Learning" [2024-08] [ICLR 2024] [paper]

• "Hybrid Active Learning with Uncertainty-Weighted Embeddings" [2024-08] [TMLR 2024] [paper]

• "SCoRe: Submodular Combinatorial Representation Learning" [2024-09] [ICML 2024] [paper]

• "FreSh: Frequency Shifting for Accelerated Neural Representation Learning" [2024-10] [ICLR 2025] [paper]

• "On Discriminative Probabilistic Modeling for Self-Supervised Representation Learning" [2024-10] [ICLR 2025] [paper]

• "When does perceptual alignment benefit vision representations?" [2024-10] [NeurIPS 2024] [paper]

• "Learning predictable and robust neural representations by straightening image sequences" [2024-11] [NeurIPS 2024] [paper]

• "One Leaf Reveals the Season: Occlusion-Based Contrastive Learning with Semantic-Aware Views for Efficient Visual Representation" [2024-11] [ICML 2025] [paper]

• "Self-supervised Transformation Learning for Equivariant Representations" [2025-02] [NeurIPS 2024] [paper]

• "Implicit Contrastive Representation Learning with Guided Stop-gradient" [2025-03] [NeurIPS 2023] [paper]

• "Self-Organizing Visual Prototypes for Non-Parametric Representation Learning" [2025-05] [ICML 2025] [paper]

• "MIM-Refiner: A Contrastive Learning Boost from Intermediate Pre-Trained Masked Image Modeling Representations" [2025-05] [ICLR 2025] [paper]

• "Maximal Matching Matters: Preventing Representation Collapse for Robust Cross-Modal Retrieval" [2025-06] [ACL 2025] [paper]

• "Region-based Cluster Discrimination for Visual Representation Learning" [2025-07] [ICCV 2025] [paper]

• "CR2PQ: Continuous Relative Rotary Positional Query for Dense Visual Representation Learning" [2025-08] [ICLR 2025] [paper]

• "LayerLock: Non-collapsing Representation Learning with Progressive Freezing" [2025-09] [ICCV 2025] [paper]

Disentanglement & Causality & Invariance

• "Weakly Supervised Disentangled Generative Causal Representation Learning" [2020-10] [ICML 2023] [paper]

• "Disentangling visual embeddings for attributes and objects" [2022-05] [CVPR 2022] [paper]

• "Simple Disentanglement of Style and Content in Visual Representations" [2023-02] [ICML 2023] [paper]

• "Leveraging sparse and shared feature activations for disentangled representation learning" [2023-04] [NeurIPS 2023] [paper]

• "Learning Structured Representations by Embedding Class Hierarchy" [2023-05] [ICLR 2023] [paper]

• "Orthogonality-Enforced Latent Space in Autoencoders: An Approach to Learning Disentangled Representations" [2023-08] [ICML 2023] [paper]

• "InfoDiffusion: Representation Learning Using Information Maximizing Diffusion Models" [2023-08] [ICML 2023] [paper]

• "Flow Factorized Representation Learning" [2023-09] [NeurIPS 2023] [paper]

• "Learning to Receive Help: Intervention-Aware Concept Embedding Models" [2023-12] [NeurIPS 2023] [paper]

• "Attribute-driven Disentangled Representation Learning for Multimodal Recommendation" [2023-12] [ACM MM 2024] [paper]

• "Exploring Diffusion Time-steps for Unsupervised Representation Learning" [2024-01] [ICLR 2024] [paper]

• "Explicitly Disentangled Representations in Object-Centric Learning" [2024-01] [TMLR 2025] [paper]

• "Unity by Diversity: Improved Representation Learning for Multimodal VAEs" [2024-02] [NeurIPS 2024] [paper]

• "Equilibrated Diffusion: Frequency-aware Textual Embedding for Equilibrated Image Customization" [2024-03] [ACM MM 2024] [paper]

• "Graph-based Unsupervised Disentangled Representation Learning via Multimodal Large Language Models" [2024-04] [NeurIPS 2024] [paper]

• "Isometric Representation Learning for Disentangled Latent Space of Diffusion Models" [2024-07] [ICML 2024] [paper]

• "Towards the Causal Complete Cause of Multi-Modal Representation Learning" [2024-07] [ICML 2025] [paper]

• "Object centric architectures enable efficient causal representation learning" [2024-07] [ICLR 2024] [paper]

• "Imaginary-Connected Embedding in Complex Space for Unseen Attribute-Object Discrimination" [2024-10] [TPAMI 2024] [paper]

• "Synergy Between Sufficient Changes and Sparse Mixing Procedure for Disentangled Representation Learning" [2025-03] [ICLR 2025] [paper]

• "Disentangled Embedding through Style and Mutual Information for Domain Generalization" [2025-07] [TMLR 2025] [paper]

Robustness, Privacy, Federated & Efficient Training

• "How to Exploit Hyperspherical Embeddings for Out-of-Distribution Detection?" [2022-03] [ICLR 2023] [paper]

• "k-Median Clustering via Metric Embedding: Towards Better Initialization with Differential Privacy" [2022-06] [NeurIPS 2023] [paper]

• "L-DAWA: Layer-wise Divergence Aware Weight Aggregation in Federated Self-Supervised Visual Representation Learning" [2023-07] [ICCV 2023] [paper]

• "DenoiseRep: Denoising Model for Representation Learning" [2024-02] [NeurIPS 2024] [paper]

• "Differentially Private Representation Learning via Image Captioning" [2024-03] [ICML 2024] [paper]

• "Data-free Neural Representation Compression with Riemannian Neural Dynamics" [2024-09] [ICML 2024] [paper]

• "Robustness Reprogramming for Representation Learning" [2024-10] [ICLR 2025] [paper]

• "BendVLM: Test-Time Debiasing of Vision-Language Embeddings" [2024-11] [NeurIPS 2024] [paper]

• "Learning to Merge Tokens via Decoupled Embedding for Efficient Vision Transformers" [2024-12] [NeurIPS 2024] [paper]

• "I0T: Embedding Standardization Method Towards Zero Modality Gap" [2024-12] [ACL 2025] [paper]

• "Gradient Extrapolation for Debiased Representation Learning" [2025-03] [ICCV 2025] [paper]

• "On the Importance of Gaussianizing Representations" [2025-05] [ICML 2025] [paper]

• "Geometry of Long-Tailed Representation Learning: Rebalancing Features for Skewed Distributions" [2025-05] [ICLR 2025] [paper]

• "TeEFusion: Blending Text Embeddings to Distill Classifier-Free Guidance" [2025-07] [ICCV 2025] [paper]

• "Learning Along the Arrow of Time: Hyperbolic Geometry for Backward-Compatible Representation Learning" [2025-07] [ICML 2025] [paper]

Semi, Weak, Few-Shot Supervision

• "Few-shot Adaptation to Distribution Shifts By Mixing Source and Target Embeddings" [2023-05] [ICML 2024] [paper]

• "An Embedding is Worth a Thousand Noisy Labels" [2025-06] [TMLR 2025] [paper]

Multimodal Training

• "Universal multimodal representation for language understanding" [2023-01] [TPAMI 2023] [paper]

• "RLEG: Vision-Language Representation Learning with Diffusion-based Embedding Generation" [2023-03] [ICML 2023] [paper]

• "Enhancing Multimodal Unified Representations for Cross Modal Generalization" [2024-03] [ACL 2025 Findings] [paper]

• "Towards Cross-modal Backward-compatible Representation Learning for Vision-Language Models" [2024-05] [ICCV 2025] [paper]

• "Multimodal Physiological Signals Representation Learning via Multiscale Contrasting for Depression Recognition" [2024-06] [ACM MM 2024] [paper]

• "MERLIN: Multimodal Embedding Refinement via LLM-based Iterative Navigation for Text-Video Retrieval-Rerank Pipeline" [2024-07] [EMNLP 2024 Industry] [paper]

• "PSM: Learning Probabilistic Embeddings for Multi-scale Zero-shot Soundscape Mapping" [2024-08] [ACM MM 2024] [paper]

• "DySarl: Dynamic Structure-Aware Representation Learning for Multimodal Knowledge Graph Reasoning" [2024-08] [ACM MM 2024] [paper]

• "Deeply Fusing Semantics and Interactions for Item Representation Learning via Topology-driven Pre-training" [2024-08] [ACM MM 2024] [paper]

• "Retrieval-based Disentangled Representation Learning with Natural Language Supervision" [2024-08] [ICLR 2024] [paper]

• "From Vision to Audio and Beyond: A Unified Model for Audio-Visual Representation and Generation" [2024-09] [ICML 2024] [paper]

• "Diving Deep into the Motion Representation of Video-Text Models" [2024-09] [ACL 2024 Findings] [paper]

• "MB2C: Multimodal Bidirectional Cycle Consistency for Learning Robust Visual Neural Representations" [2024-10] [ACM MM 2024] [paper]

• "Cross-Lingual Representation Alignment Through Contrastive Image-Caption Tuning" [2025-05] [ACL 2025] [paper]

• "Kernel-based Unsupervised Embedding Alignment for Enhanced Visual Representation in Vision-language Models" [2025-06] [ICML 2025] [paper]

• "DALR: Dual-level Alignment Learning for Multimodal Sentence Representation Learning" [2025-06] [ACL 2025 Findings] [paper]

3.3 Datasets & Benchmarks

• "How robust is unsupervised representation learning to distribution shift?" [2022-06] [ICLR 2023] [paper]

• "Self-supervised learning of Split Invariant Equivariant representations" [2023-02] [ICML 2023] [paper]

• "Unicom: Universal and Compact Representation Learning for Image Retrieval" [2023-02] [ICLR 2023] [paper]

• "A Large-scale Study of Spatiotemporal Representation Learning with a New Benchmark on Action Recognition" [2023-03] [ICCV 2023] [paper]

• "PLIP: Language-Image Pre-training for Person Representation Learning" [2023-05] [NeurIPS 2024] [paper]

• "Babel-ImageNet: Massively Multilingual Evaluation of Vision-and-Language Representations" [2023-06] [ACL 2024] [paper]

• "Cross-Domain Product Representation Learning for Rich-Content E-Commerce" [2023-08] [ICCV 2023] [paper]

• "PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning" [2023-08] [NeurIPS 2023] [paper]

• "RankMe: Assessing the Downstream Performance of Pretrained Self-Supervised Representations by Their Rank" [2023-08] [ICML 2023] [paper]

• "Towards Universal Image Embeddings: A Large-Scale Dataset and Challenge for Generic Image Representations" [2023-09] [ICCV 2023] [paper]

• "FORB: A Flat Object Retrieval Benchmark for Universal Image Embedding" [2023-09] [NeurIPS 2023] [paper]

• "SciMMIR: Benchmarking Scientific Multi-modal Information Retrieval" [2024-01] [ACL 2024 Findings] [paper]

• "Mapping the Multiverse of Latent Representations" [2024-02] [ICML 2024] [paper]

• "TorchSpatial: A Location Encoding Framework and Benchmark for Spatial Representation Learning" [2024-06] [NeurIPS 2024] [paper]

• "HyperFace: Generating Synthetic Face Recognition Datasets by Exploring Face Embedding Hypersphere" [2024-11] [ICLR 2025] [paper]

• "Scendi Score: Prompt-Aware Diversity Evaluation via Schur Complement of CLIP Embeddings" [2024-12] [ICCV 2025] [paper]

• "SEA: Low-Resource Safety Alignment for Multimodal Large Language Models via Synthetic Embeddings" [2025-02] [ACL 2025] [paper]

• "Can LLMs Deceive CLIP? Benchmarking Adversarial Compositionality of Pre-trained Multimodal Representation via Text Updates" [2025-05] [ACL 2025] [paper]

• "On the Transfer of Object-Centric Representation Learning" [2025-05] [ICLR 2025] [paper]

• "Learning Fine-Grained Representations through Textual Token Disentanglement in Composed Video Retrieval" [2025-07] [ICLR 2025] [paper]

• "Color Me Correctly: Bridging Perceptual Color Spaces and Text Embeddings for Improved Diffusion Generation" [2025-09] [ACM MM 2025] [paper]

3.4 Embedding Analysis

Representation Properties & Mechanisms

• "Your Contrastive Learning Is Secretly Doing Stochastic Neighbor Embedding" [2022-05] [ICLR 2023] [paper]

• "Bag of Image Patch Embedding Behind the Success of Self-Supervised Learning" [2022-06] [TMLR 2023] [paper]

• "Learning Efficient Coding of Natural Images with Maximum Manifold Capacity Representations" [2023-03] [NeurIPS 2023] [paper]

• "Neural Harmonics: Bridging Spectral Embedding and Matrix Completion in Self-Supervised Learning" [2023-05] [NeurIPS 2023] [paper]

• "Are Neurons Actually Collapsed? On the Fine-Grained Structure in Neural Representations" [2023-06] [ICML 2023] [paper]

• "Improving neural network representations using human similarity judgments" [2023-06] [NeurIPS 2023] [paper]

• "Is a Caption Worth a Thousand Images? A Study on Representation Learning" [2023-07] [ICLR 2023] [paper]

• "ViLLA: Fine-Grained Vision-Language Representation Learning from Real-World Data" [2023-08] [ICCV 2023] [paper]

• "Analyzing Vision Transformers for Image Classification in Class Embedding Space" [2023-10] [NeurIPS 2023] [paper]

• "RanDumb: Random Representations Outperform Online Continually Learned Representations" [2024-02] [NeurIPS 2024] [paper]

• "Embedding Dimension of Contrastive Learning and k-Nearest Neighbors" [2024-02] [NeurIPS 2024] [paper]

• "A representation-learning game for classes of prediction tasks" [2024-03] [ICLR 2024] [paper]

• "Weighted Point Set Embedding for Multimodal Contrastive Learning Toward Optimal Similarity Metric" [2024-04] [ICLR 2025] [paper]

• "Transport of Algebraic Structure to Latent Embeddings" [2024-05] [ICML 2024] [paper]

• "Decomposing and Interpreting Image Representations via Text in ViTs Beyond CLIP" [2024-06] [NeurIPS 2024] [paper]

• "Preserving Pre-trained Representation Space: On Effectiveness of Prefix-tuning for Large Multi-modal Models" [2024-06] [EMNLP 2024 Findings] [paper]

• "Prompt-Softbox-Prompt: A Free-Text Embedding Control for Image Editing" [2024-08] [ACM MM 2025] [paper]

• "Intriguing Properties of Hyperbolic Embeddings in Vision-Language Models" [2024-08] [TMLR 2024] [paper]

• "Implicit Neural Representations and the Algebra of Complex Wavelets" [2024-08] [ICLR 2024] [paper]

• "A Cat Is A Cat (Not A Dog!): Unraveling Information Mix-ups in Text-to-Image Encoders through Causal Analysis and Embedding Optimization" [2024-10] [NeurIPS 2024] [paper]

• "Semantic Token Reweighting for Interpretable and Controllable Text Embeddings in CLIP" [2024-10] [EMNLP 2024 Findings] [paper]

• "Investigating the Benefits of Projection Head for Representation Learning" [2024-10] [ICLR 2024] [paper]

• "Narrowing Information Bottleneck Theory for Multimodal Image-Text Representations Interpretability" [2025-02] [ICLR 2025] [paper]

• "Generalization Guarantees for Representation Learning via Data-Dependent Gaussian Mixture Priors" [2025-02] [ICLR 2025] [paper]

• "Feature Learning beyond the Lazy-Rich Dichotomy: Insights from Representational Geometry" [2025-03] [ICML 2025] [paper]

• "A Unifying Framework for Representation Learning" [2025-05] [ICLR 2025] [paper]

• "On the Similarities of Embeddings in Contrastive Learning" [2025-06] [ICML 2025] [paper]

• "Disappearance of Timestep Embedding: A Case Study on Neural ODE and Diffusion Models" [2025-06] [TMLR 2025] [paper]

• "Discovering Divergent Representations between Text-to-Image Models" [2025-09] [ICCV 2025] [paper]

Robustness & Human Alignment

• "Self-supervised video pretraining yields robust and more human-aligned visual representations" [2022-10] [NeurIPS 2023] [paper]

• "Embedding an Ethical Mind: Aligning Text-to-Image Synthesis via Lightweight Value Optimization" [2024-10] [ACM MM 2024] [paper]

• "PRISM: Reducing Spurious Implicit Biases in Vision-Language Models with LLM-Guided Embedding Projection" [2025-07] [ICCV 2025] [paper]

Interpretability

• "Identifying Interpretable Subspaces in Image Representations" [2023-08] [ICML 2023] [paper]

• "Interpreting CLIP's Image Representation via Text-Based Decomposition" [2023-10] [ICLR 2024] [paper]

• "Interpreting CLIP with Sparse Linear Concept Embeddings (SpLiCE)" [2024-02] [NeurIPS 2024] [paper]

• "Finding NEM-U: Explaining unsupervised representation learning through neural network generated explanation masks" [2024-09] [ICML 2024] [paper]

• "AKRMap: Adaptive Kernel Regression for Trustworthy Visualization of Cross-Modal Embeddings" [2025-05] [ICML 2025] [paper]

• "Enhancing Pre-trained Representation Classifiability can Boost its Interpretability" [2025-10] [ICLR 2025] [paper]

3.5 Embedding Applications

Segmentation & Detection

• "Referring Image Segmentation via Joint Mask Contextual Embedding Learning and Progressive Alignment Network" [2023-04] [EMNLP 2023] [paper]

• "Cross Paradigm Representation and Alignment Transformer for Image Deraining" [2025-04] [ACM MM 2025] [paper]

Retrieval & Reranking

• "TempCLR: Temporal Alignment Representation with Contrastive Learning" [2023-07] [ICLR 2023] [paper]

• "Unifying Multimodal Retrieval via Document Screenshot Embedding" [2024-06] [EMNLP 2024] [paper]

• "CLaMP 2: Multimodal Music Information Retrieval Across 101 Languages Using Large Language Models" [2024-10] [NAACL 2025 Findings] [paper]

• "Towards Storage-Efficient Visual Document Retrieval: An Empirical Study on Reducing Patch-Level Embeddings" [2025-06] [ACL 2025 Findings] [paper]

• "Modeling Uncertainty in Composed Image Retrieval via Probabilistic Embeddings" [2025-07] [ACL 2025] [paper]

• "Queries Are Not Alone: Clustering Text Embeddings for Video Search" [2025-10] [SIGIR 2025] [paper]

Identification & Surveillance

• "Identity-Seeking Self-Supervised Representation Learning for Generalizable Person Re-Identification" [2023-08] [ICCV 2023] [paper]

• "Camera-Driven Representation Learning for Unsupervised Domain Adaptive Person Re-identification" [2023-08] [ICCV 2023] [paper]

• "Learning Continual Compatible Representation for Re-indexing Free Lifelong Person Re-identificationç" [2024-03] [CVPR 2024] [paper]

Autonomous Driving

• "Unsupervised Self-Driving Attention Prediction via Uncertainty Mining and Knowledge Embedding" [2023-03] [ICCV 2023] [paper]

• "FreqPDE: Rethinking Positional Depth Embedding for Multi-View 3D Object Detection Transformers" [2025-10] [ICCV 2025] [paper]

Enhancement & Generation & Editing

• "StegaNeRF: Embedding Invisible Information within Neural Radiance Fields" [2022-12] [ICCV 2023] [paper]

• "DiffV2S: Diffusion-Based Video-to-Speech Synthesis with Vision-Guided Speaker Embedding" [2023-08] [ICCV 2023] [paper]

• "GAN-based Symmetric Embedding Costs Adjustment for Enhancing Image Steganographic Security" [2024-03] [ACM MM 2024] [paper]

• "CLIPAway: Harmonizing focused embeddings for removing objects via diffusion models" [2024-06] [NeurIPS 2024] [paper]

• "Addressing Text Embedding Leakage in Diffusion-based Image Editing" [2024-12] [ICCV 2025] [paper]

• "DRC: Enhancing Personalized Image Generation via Disentangled Representation Composition" [2025-04] [ACM MM 2025] [paper]

• "StereoINR: Cross-View Geometry Consistent Stereo Super Resolution with Implicit Neural Representation" [2025-05] [ACM MM 2025] [paper]

• "LightBSR: Towards Lightweight Blind Super-Resolution via Discriminative Implicit Degradation Representation Learning" [2025-06] [ICCV 2025] [paper]

• "LotteryCodec: Searching the Implicit Representation in a Random Network for Low-Complexity Image Compression" [2025-07] [ICML 2025] [paper]

• "Text Embedding Knows How to Quantize Text-Guided Diffusion Models" [2025-07] [ICCV 2025] [paper]

• "Translation of Text Embedding via Delta Vector to Suppress Strongly Entangled Content in Text-to-Image Diffusion Models" [2025-08] [ICCV 2025] [paper]

Others

• "Multi-Level Information Retrieval Augmented Generation for Knowledge-based Visual Question Answering" [2024-06] [EMNLP 2024] [paper]

• "Autogenic Language Embedding for Coherent Point Tracking" [2024-07] [ACM MM 2024] [paper]

• "Hierarchical Visual Categories Modeling: A Joint Representation Learning and Density Estimation Framework for Out-of-Distribution Detection" [2024-08] [ICCV 2023] [paper]

• "Dual Advancement of Representation Learning and Clustering for Sparse and Noisy Images" [2024-09] [ACM MM 2024] [paper]

• "DeSPITE: Exploring Contrastive Deep Skeleton-Pointcloud-IMU-Text Embeddings for Advanced Point Cloud Human Activity Understanding" [2025-06] [ICCV 2025] [paper]

• "Multimodal Invariant Sentiment Representation Learning" [2025-07] [ACL 2025 Findings] [paper]

• "GT-Loc: Unifying When and Where in Images through a Joint Embedding Space" [2025-07] [ICCV 2025] [paper]

• "MiraGe: Multimodal Discriminative Representation Learning for Generalizable AI-Generated Image Detection" [2025-08] [ACM MM 2025] [paper]

• "DRKF: Decoupled Representations with Knowledge Fusion for Multimodal Emotion Recognition" [2025-08] [ACM MM 2025] [paper]

4. Audio Embedding

4.1 Models

Speaker Embedding

• "High-Resolution Embedding Extractor for Speaker Diarisation" [2022-11] [ICASSP 2023] [paper]

• "ECAPA++: Fine-grained Deep Embedding Learning for TDNN Based Speaker Verification" [2023-05] [InterSpeech 2023] [paper]

• "Frame-Wise and Overlap-Robust Speaker Embeddings for Meeting Diarization" [2023-06] [ICASSP 2023] [paper]

• "Ordered and Binary Speaker Embedding" [2023-06] [InterSpeech 2023] [paper]

• "Contrastive Speaker Embedding With Sequential Disentanglement" [2023-09] [ICASSP 2024] [paper]

• "Multi-View Speaker Embedding Learning for Enhanced Stability and Discriminability" [2024-05] [ICASSP 2024] [paper]

• "SVSNet+: Enhancing Speaker Voice Similarity Assessment Models with Representations from Speech Foundation Models" [2024-06] [InterSpeech 2024] [paper]

• "Residual Speaker Representation for One-Shot Voice Conversion" [2024-09] [InterSpeech 2024] [paper]

• "Guided Speaker Embedding" [2024-10] [ICASSP 2025] [paper]

• "SEED: Speaker Embedding Enhancement Diffusion Model" [2025-05] [InterSpeech 2025] [paper]

• "Codec-ASV: Exploring Neural Audio Codec For Speaker Representation Learning" [2025-07] [ICASSP 2025] [paper]

• "Diarization-Guided Multi-Speaker Embeddings" [2025-09] [InterSpeech 2025] [paper]

General Speech Representation

• "Robust Data2VEC: Noise-Robust Speech Representation Learning for ASR by Combining Regression and Improved Contrastive Learning" [2022-10] [ICASSP 2023] [paper]

• "An Improved Optimal Transport Kernel Embedding Method with Gating Mechanism for Singing Voice Separation and Speaker Identification" [2023-01] [ICASSP 2023] [paper]

• "DinoSR: Self-Distillation and Online Clustering for Self-supervised Speech Representation Learning" [2023-05] [NeurIPS 2023] [paper]

• "Masked Modeling Duo for Speech: Specializing General-Purpose Audio Representation to Speech using Denoising Distillation" [2023-05] [InterSpeech 2023] [paper]

• "MT4SSL: Boosting Self-Supervised Speech Representation Learning by Integrating Multiple Targets" [2023-06] [InterSpeech 2023] [paper]

• "Towards Effective and Compact Contextual Representation for Conformer Transducer Speech Recognition Systems" [2023-06] [InterSpeech 2023] [paper]

• "Self-Supervised Acoustic Word Embedding Learning via Correspondence Transformer Encoder" [2023-07] [InterSpeech 2023] [paper]

• "CoBERT: Self-Supervised Speech Representation Learning Through Code Representation Learning" [2023-08] [InterSpeech 2023] [paper]

• "RepCodec: A Speech Representation Codec for Speech Tokenization" [2023-08] [ACL 2024] [paper]

• "Unsupervised Learning of Discrete Latent Representations with Data-Adaptive Dimensionality from Continuous Speech Streams" [2023-08] [InterSpeech 2023] [paper]

• "Self-supervised Neural Factor Analysis for Disentangling Utterance-level Speech Representations" [2023-08] [ICML 2023] [paper]

• "EnCodecMAE: leveraging neural codecs for universal audio representation learning" [2023-09] [InterSpeech 2025] [paper]

• "Audio Barlow Twins: Self-Supervised Audio Representation Learning" [2023-09] [ICASSP 2023] [paper]

• "R-Spin: Efficient Speaker and Noise-invariant Representation Learning with Acoustic Pieces" [2023-11] [NAACL 2024] [paper]

• "Spoken Word2Vec: Learning Skipgram Embeddings from Speech" [2023-11] [InterSpeech 2024] [paper]

• "Enc-Dec RNN Acoustic Word Embeddings learned via Pairwise Prediction" [2023-11] [InterSpeech 2023] [paper]

• "Language-Codec: Bridging Discrete Codec Representations and Speech Language Models" [2024-02] [ACL 2025] [paper]

• "Audio Mamba: Selective State Spaces for Self-Supervised Audio Representations" [2024-06] [InterSpeech 2024] [paper]

• "MS-HuBERT: Mitigating Pre-training and Inference Mismatch in Masked Language Modelling methods for learning Speech Representations" [2024-06] [InterSpeech 2024] [paper]

• "MMM: Multi-Layer Multi-Residual Multi-Stream Discrete Speech Representation from Self-supervised Learning Model" [2024-06] [InterSpeech 2024] [paper]

• "AxLSTMs: learning self-supervised audio representations with xLSTMs" [2024-08] [InterSpeech 2025] [paper]

• "Compositional Audio Representation Learning" [2024-09] [ICASSP 2025] [paper]

• "Sylber: Syllabic Embedding Representation of Speech from Raw Audio" [2024-10] [ICLR 2025] [paper]

• "UniWav: Towards Unified Pre-training for Speech Representation Learning and Generation" [2025-03] [ICLR 2025] [paper]

• "LiSTEN: Learning Soft Token Embeddings for Neural Audio LLMs" [2025-05] [InterSpeech 2025] [paper]

• "Spectrotemporal Modulation: Efficient and Interpretable Feature Representation for Classifying Speech, Music, and Environmental Sounds" [2025-05] [InterSpeech 2025] [paper]

• "Representing Speech Through Autoregressive Prediction of Cochlear Tokens" [2025-08] [InterSpeech 2025] [paper]

Speech Content, Phoneme & Articulatory Representation

• "Learning to Compute the Articulatory Representations of Speech with the MIRRORNET" [2022-10] [InterSpeech 2023] [paper]

• "Improving Bilingual TTS Using Language And Phonology Embedding With Embedding Strength Modulator" [2022-12] [InterSpeech 2023] [paper]

• "TranUSR: Phoneme-to-word Transcoder Based Unified Speech Representation Learning for Cross-lingual Speech Recognition" [2023-05] [InterSpeech 2023] [paper]

• "XPhoneBERT: A Pre-trained Multilingual Model for Phoneme Representations for Text-to-Speech" [2023-05] [InterSpeech 2023] [paper]

• "Deep Speech Synthesis from MRI-Based Articulatory Representations" [2023-07] [InterSpeech 2023] [paper]

• "Discovering Phonetic Feature Event Patterns in Transformer Embeddings" [2023-10] [InterSpeech 2023] [paper]

• "Are Articulatory Feature Overlaps Shrouded in Speech Embeddings?" [2024-05] [InterSpeech 2024] [paper]

• "SingOMD: Singing Oriented Multi-resolution Discrete Representation Construction from Speech Models" [2024-06] [InterSpeech 2024] [paper]

• "Neurodyne: Neural Pitch Manipulation with Representation Learning and Cycle-Consistency GAN" [2025-05] [InterSpeech 2025] [paper]

• "Binary Representation Learning for Discriminative Acoustic Unit Discovery" [2025-07] [ICASSP 2025] [paper]

• "Learning Optimal Prosody Embedding Codebook based on F0 and Energy" [2025-08] [InterSpeech 2025] [paper]

• "ASDA: Audio Spectrogram Differential Attention Mechanism for Self-Supervised Representation Learning" [2025-08] [InterSpeech 2025] [paper]

Emotion, Paralinguistic & Prosody Embedding

• "Self-FiLM: Conditioning GANs with self-supervised representations for bandwidth extension based speaker recognition" [2023-01] [InterSpeech 2023] [paper]

• "Learning Representation of Therapist Empathy in Counseling Conversation Using Siamese Hierarchical Attention Network" [2023-05] [InterSpeech 2024] [paper]

• "FusedF0: Improving DNN-based F0 Estimation by Fusion of Summary-Correlograms and Raw Waveform Representations of Speech Signals" [2023-06] [InterSpeech 2023] [paper]

• "Improved Contextualized Speech Representations for Tonal Analysis" [2023-06] [InterSpeech 2023] [paper]

• "Speech Synthesis with Self-Supervisedly Learnt Prosodic Representations" [2023-08] [InterSpeech 2023] [paper]

• "Revealing Emotional Clusters in Speaker Embeddings: A Contrastive Learning Strategy for Speech Emotion Recognition" [2024-01] [ICASSP 2024] [paper]

• "Speech-Driven Emotional 3d Talking Face Animation Using Emotional Embeddings" [2024-01] [ICASSP 2024] [paper]

• "Adaptive Speech Emotion Representation Learning Based On Dynamic Graph" [2024-05] [ICASSP 2024] [paper]

• "emotion2vec: Self-Supervised Pre-Training for Speech Emotion Representation" [2024-06] [ACL 2024 Findings] [paper]

• "Emotion-Aware Speech Self-Supervised Representation Learning with Intensity Knowledge" [2024-09] [InterSpeech 2024] [paper]

• "EmoSphere-SER: Enhancing Speech Emotion Recognition Through Spherical Representation with Auxiliary Classification" [2025-05] [InterSpeech 2025] [paper]

• "HYFuse: Aligning Heterogeneous Speech Pre-Trained Representations in Hyperbolic Space for Speech Emotion Recognition" [2025-06] [InterSpeech 2025] [paper]

• "MATER: Multi-level Acoustic and Textual Emotion Representation for Interpretable Speech Emotion Recognition" [2025-06] [InterSpeech 2025] [paper]

• "SupraDoRAL: Automatic Word Prominence Detection Using Suprasegmental Dependencies of Representations with Acoustic and Linguistic Context" [2025-08] [InterSpeech 2025] [paper]

Multilingual Embedding

• "DistilXLSR: A Light Weight Cross-Lingual Speech Representation Model" [2023-06] [InterSpeech 2023] [paper]

• "DSE-TTS: Dual Speaker Embedding for Cross-Lingual Text-to-Speech" [2023-06] [InterSpeech 2023] [paper]

• "Conformer-based Language Embedding with Self-Knowledge Distillation for Spoken Language Identification" [2023-06] [InterSpeech 2023] [paper]

• "Language-Universal Phonetic Representation in Multilingual Speech Pretraining for Low-Resource Speech Recognition" [2023-06] [InterSpeech 2023] [paper]

• "MUST&P-SRL: Multi-lingual and Unified Syllabification in Text and Phonetic Domains for Speech Representation Learning" [2023-10] [EMNLP 2023 Industry] [paper]

• "Wave to Interlingua: Analyzing Representations of Multilingual Speech Transformers for Spoken Language Translation" [2024-05] [InterSpeech 2024] [paper]

• "AfriHuBERT: A self-supervised speech representation model for African languages" [2024-09] [InterSpeech 2025] [paper]

Multimodal

• "ImagineNet: Target Speaker Extraction with Intermittent Visual Cue Through Embedding Inpainting" [2022-10] [ICASSP 2023] [paper]

• "Jointly Learning Visual and Auditory Speech Representations from Raw Data" [2022-12] [ICLR 2023] [paper]

• "Continuous Interaction with A Smart Speaker via Low-Dimensional Embeddings of Dynamic Hand Pose" [2023-02] [ICASSP 2023] [paper]

• "ModEFormer: Modality-Preserving Embedding for Audio-Video Synchronization using Transformers" [2023-03] [ICASSP 2023] [paper]

• "ChatGPT-EDSS: Empathetic Dialogue Speech Synthesis Trained from ChatGPT-derived Context Word Embeddings" [2023-05] [InterSpeech 2023] [paper]

• "MIR-GAN: Refining Frame-Level Modality-Invariant Representations with Adversarial Network for Audio-Visual Speech Recognition" [2023-06] [ACL 2023] [paper]

• "Fusion of Audio and Visual Embeddings for Sound Event Localization and Detection" [2023-12] [ICASSP 2024] [paper]

• "EnCLAP: Combining Neural Audio Codec and Audio-Text Joint Embedding for Automated Audio Captioning" [2024-01] [ICASSP 2024] [paper]

• "Invariant Motion Representation Learning for 3D Talking Face Synthesis" [2024-01] [ICASSP 2024] [paper]

• "M2D-CLAP: Masked Modeling Duo Meets CLAP for Learning General-purpose Audio-Language Representation" [2024-06] [InterSpeech 2024] [paper]

• "Audio-text Retrieval with Transformer-based Hierarchical Alignment and Disentangled Cross-modal Representation" [2024-09] [InterSpeech 2024] [paper]

• "Learning Spatially-Aware Language and Audio Embeddings" [2024-09] [NeurIPS 2024] [paper]

• "XLAVS-R: Cross-Lingual Audio-Visual Speech Representation Learning for Noise-Robust Speech Perception" [2024-10] [ACL 2024] [paper]

• "Vela: Scalable Embeddings with Voice Large Language Models for Multimodal Retrieval" [2025-06] [InterSpeech 2025] [paper]

• "SKE-MSA: Enhancing Representation Learning with VAD Lexicon for Multimodal Sentiment Analysis" [2025-08] [ICASSP 2025] [paper]

4.2 Training Methods

Disentanglement & Decoupling

• "Disentangling Speech from Surroundings with Neural Embeddings" [2022-03] [ICASSP 2023] [paper]

• "CCSRD: Content-Centric Speech Representation Disentanglement Learning for End-to-End Speech Translation" [2023-04] [EMNLP 2023 Findings] [paper]

• "Mutual Information-based Embedding Decoupling for Generalizable Speaker Verification" [2023-04] [InterSpeech 2023] [paper]

• "Self-supervised Fine-tuning for Improved Content Representations by Speaker-invariant Clustering" [2023-05] [InterSpeech 2023] [paper]

• "Disentangled Representation Learning for Multilingual Speaker Recognition" [2023-06] [InterSpeech 2023] [paper]

• "MT-SLVR: Multi-Task Self-Supervised Learning for Transformation In(Variant) Representations" [2023-07] [InterSpeech 2023] [paper]

• "Generalizable Zero-Shot Speaker Adaptive Speech Synthesis with Disentangled Representations" [2023-08] [InterSpeech 2023] [paper]

• "Disentangled Representation Learning for Environment-agnostic Speaker Recognition" [2024-05] [InterSpeech 2024] [paper]

• "Disentangling prosody and timbre embeddings via voice conversion" [2024-09] [InterSpeech 2024] [paper]

• "Universal Semantic Disentangled Privacy-preserving Speech Representation Learning" [2025-05] [InterSpeech 2025] [paper]

• "DiEmo-TTS: Disentangled Emotion Representations via Self-Supervised Distillation for Cross-Speaker Emotion Transfer in Text-to-Speech" [2025-05] [InterSpeech 2025] [paper]

• "HASRD: Hierarchical Acoustic and Semantic Representation Disentanglement" [2025-06] [InterSpeech 2025] [paper]

Contrastive, Generative & Multi-Objective Learning

• "Spectral Clustering-Aware Learning of Embeddings for Speaker Diarisation" [2022-10] [ICASSP 2023] [paper]

• "Simultaneously Learning Robust Audio Embeddings and balanced Hash codes for Query-by-Example" [2022-11] [ICASSP 2023] [paper]

• "Contrastive Representation Learning for Acoustic Parameter Estimation" [2023-02] [ICASSP 2023] [paper]

• "Joint Generative-Contrastive Representation Learning for Anomalous Sound Detection" [2023-05] [ICASSP 2023] [paper]

• "Pushing the Limits of Unsupervised Unit Discovery for SSL Speech Representation" [2023-06] [InterSpeech 2023] [paper]

• "Semantic Enrichment Towards Efficient Speech Representations" [2023-06] [InterSpeech 2023] [paper]

• "ReCLR: Reference-Enhanced Contrastive Learning of Audio Representation for Depression Detection" [2023-06] [InterSpeech 2023] [paper]

• "On The Effect Of Data-Augmentation On Local Embedding Properties In The Contrastive Learning Of Music Audio Representations" [2024-01] [ICASSP 2024] [paper]

• "Embedding Learning for Preference-based Speech Quality Assessment" [2024-05] [InterSpeech 2024] [paper]

• "Articulatory synthesis using representations learnt through phonetic label-aware contrastive loss" [2024-05] [InterSpeech 2024] [paper]

• "Refining Self-supervised Learnt Speech Representation using Brain Activations" [2024-06] [InterSpeech 2024] [paper]

• "LASER: Learning by Aligning Self-supervised Representations of Speech for Improving Content-related Tasks" [2024-06] [InterSpeech 2024] [paper]

• "Towards Robust Few-shot Class Incremental Learning in Audio Classification using Contrastive Representation" [2024-07] [InterSpeech 2024] [paper]

• "Neural Compression Augmentation for Contrastive Audio Representation Learning" [2024-09] [InterSpeech 2024] [paper]

• "REWIND: Speech Time Reversal for Enhancing Speaker Representations in Diffusion-based Voice Conversion" [2025-05] [InterSpeech 2025] [paper]

• "InfoMin-based Query Embedding Optimization For Query-based Universal Sound Separation" [2025-07] [ICASSP 2025] [paper]

• "Enhancing Target-speaker Automatic Speech Recognition Using Multiple Speaker Embedding Extractors with Virtual Speaker Embedding" [2025-08] [InterSpeech 2025] [paper]

Distillation, Pruning & Efficiency-Oriented Training

• "Application of Knowledge Distillation to Multi-Task Speech Representation Learning" [2022-10] [InterSpeech 2023] [paper]

• "Self-Supervised Speech Representation Learning for Keyword-Spotting With Light-Weight Transformers" [2023-01] [ICASSP 2023] [paper]

• "Masking Kernel for Learning Energy-Efficient Representations for Speaker Recognition and Mobile Health" [2023-02] [InterSpeech 2023] [paper]

• "Automatic Data Augmentation for Domain Adapted Fine-Tuning of Self-Supervised Speech Representations" [2023-06] [InterSpeech 2023] [paper]

• "Task-Agnostic Structured Pruning of Speech Representation Models" [2023-06] [InterSpeech 2023] [paper]

• "On-Device Constrained Self-Supervised Speech Representation Learning for Keyword Spotting via Knowledge Distillation" [2023-07] [InterSpeech 2023] [paper]

• "Knowledge Distillation from Self-Supervised Representation Learning Model with Discrete Speech Units for Any-to-Any Streaming Voice Conversion" [2024-05] [InterSpeech 2024] [paper]

• "DAISY: Data Adaptive Self-Supervised Early Exit for Speech Representation Models" [2024-06] [InterSpeech 2024] [paper]

• "PRVAE-VC2: Non-Parallel Voice Conversion by Distillation of Speech Representations" [2024-09] [InterSpeech 2024] [paper]

• "EH-MAM: Easy-to-Hard Masked Acoustic Modeling for Self-Supervised Speech Representation Learning" [2024-10] [EMNLP 2024] [paper]

• "DuRep: Dual-Mode Speech Representation Learning via ASR-Aware Distillation" [2025-05] [InterSpeech 2025] [paper]

• "Metric Learning with Progressive Self-Distillation for Audio-Visual Embedding Learning" [2025-07] [ICASSP 2025] [paper]

Multilingual Training

• "Leveraging Language Embeddings for Cross-lingual Self-supervised Speech Representation Learning" [2023-01] [ICASSP 2023] [paper]

• "Acoustic Word Embeddings for Untranscribed Target Languages with Continued Pretraining and Learned Pooling" [2023-06] [InterSpeech 2023] [paper]

• "Embedding Articulatory Constraints for Low-resource Speech Recognition Based on Large Pre-trained Model" [2023-06] [InterSpeech 2023] [paper]

• "Towards Robust Speech Representation Learning for Thousands of Languages" [2024-06] [EMNLP 2024] [paper]

• "Introducing Multilingual Phonetic Information to Speaker Embedding for Speaker Verification" [2024-09] [ICASSP 2024] [paper]

Privacy-Preserving Representation Learning

• "Utility-Preserving Privacy-Enabled Speech Embeddings for Emotion Detection" [2023-06] [InterSpeech 2023] [paper]

• "Privacy-preserving Representation Learning for Speech Understanding" [2023-06] [InterSpeech 2023] [paper]

• "On-Device Speaker Anonymization of Acoustic Embeddings for ASR based on Flexible Location Gradient Reversal Layer" [2023-07] [InterSpeech 2023] [paper]

• "Asynchronous Voice Anonymization Using Adversarial Perturbation On Speaker Embedding" [2024-06] [InterSpeech 2024] [paper]

• "Eta-WavLM: Efficient Speaker Identity Removal in Self-Supervised Speech Representations Using a Simple Linear Equation" [2025-05] [ACL 2025 Findings] [paper]

• "WavShape: Information-Theoretic Speech Representation Learning for Fair and Privacy-Aware Audio Processing" [2025-06] [InterSpeech 2025] [paper]

• "Privacy-Preserving Speaker Verification via End-to-End Secure Representation Learning" [2025-08] [InterSpeech 2025] [paper]

Robustness-Oriented Training

• "Learning Emotional Representations from Imbalanced Speech Data for Speech Emotion Recognition and Emotional Text-to-Speech" [2023-06] [InterSpeech 2023] [paper]

• "Downstream Task Agnostic Speech Enhancement with Self-Supervised Representation Loss" [2023-06] [InterSpeech 2023] [paper]

• "Don’t Stop Self-Supervision: Accent Adaptation of Speech Representations via Residual Adapters" [2023-07] [InterSpeech 2023] [paper]

• "Rethinking Session Variability: Leveraging Session Embeddings for Session Robustness in Speaker Verification" [2023-09] [ICASSP 2024] [paper]

• "Learning Repeatable Speech Embeddings Using An Intra-class Correlation Regularizer" [2023-10] [NeurIPS 2023] [paper]

• "CA-SSLR: Condition-Aware Self-Supervised Learning Representation for Generalized Speech Processing" [2024-02] [NeurIPS 2024] [paper]

• "Real-time scheme for rapid extraction of speaker embeddings in challenging recording conditions" [2024-05] [InterSpeech 2024] [paper]

• "Tackling Missing Modalities in Audio-Visual Representation Learning Using Masked Autoencoders" [2024-09] [InterSpeech 2024] [paper]

• "Balanced-Wav2Vec: Enhancing Stability and Robustness of Representation Learning Through Sample Reweighting Techniques" [2024-09] [InterSpeech 2024] [paper]

• "Multi-Task Corrupted Prediction for Learning Robust Audio-Visual Speech Representation" [2025-01] [ICLR 2025] [paper]

• "Mitigating Non-Target Speaker Bias in Guided Speaker Embedding" [2025-06] [InterSpeech 2025] [paper]

• "Inter- and Intra-Sentence Cuer-Invariant Representation Learning for Generalizable Cued Speech Recognition" [2025-07] [ICASSP 2025] [paper]

• "Robust Target Speaker Diarization and Separation via Augmented Speaker Embedding Sampling" [2025-08] [InterSpeech 2025] [paper]

• "Adaptive Across-Subcenter Representation Learning for Imbalanced Anomalous Sound Detection" [2025-09] [InterSpeech 2025] [paper]

Other Methods

• "Semi-supervised Learning for Continuous Emotional Intensity Controllable Speech Synthesis with Disentangled Representations" [2022-11] [InterSpeech 2023] [paper]

• "Adapting Self-Supervised Models to Multi-Talker Speech Recognition Using Speaker Embeddings" [2023-01] [ICASSP 2023] [paper]

• "Design Choices for Learning Embeddings from Auxiliary Tasks for Domain Generalization in Anomalous Sound Detection" [2023-01] [ICASSP 2023] [paper]

• "Incorporating Uncertainty from Speaker Embedding Estimation to Speaker Verification" [2023-02] [ICASSP 2023] [paper]

• "Transforming the Embeddings: A Lightweight Technique for Speech Emotion Recognition Tasks" [2023-03] [InterSpeech 2023] [paper]

• "Label Aware Speech Representation Learning For Language Identification" [2023-06] [InterSpeech 2023] [paper]

• "Emotion Label Encoding Using Word Embeddings for Speech Emotion Recognition" [2023-06] [InterSpeech 2023] [paper]

• "Towards Paralinguistic-Only Speech Representations for End-to-End Speech Emotion Recognition" [2023-06] [InterSpeech 2023] [paper]

• "Improving Joint Speech-Text Representations Without Alignment" [2023-08] [InterSpeech 2023] [paper]

• "LABERT: A Combination of Local Aggregation and Self-Supervised Speech Representation Learning for Detecting Informative Hidden Units in Low-Resource ASR Systems" [2023-08] [InterSpeech 2023] [paper]

• "Dual Acoustic Linguistic Self-supervised Representation Learning for Cross-Domain Speech Recognition" [2023-08] [InterSpeech 2023] [paper]

• "Text-Only Domain Adaptation for End-to-End Speech Recognition through Down-Sampling Acoustic Representation" [2023-09] [InterSpeech 2023] [paper]

• "MixRep: Hidden Representation Mixup for Low-Resource Speech Recognition" [2023-10] [InterSpeech 2023] [paper]

• "Adapter-tuning with Effective Token-dependent Representation Shift for Automatic Speech Recognition" [2023-11] [InterSpeech 2023] [paper]

• "Consistent and Relevant: Rethink the Query Embedding in General Sound Separation" [2023-12] [ICASSP 2024] [paper]

• "GR0: Self-Supervised Global Representation Learning for Zero-Shot Voice Conversion" [2024-03] [ICASSP 2024] [paper]

• "ASTRA: Aligning Speech and Text Representations for Asr without Sampling" [2024-05] [InterSpeech 2024] [paper]

• "Challenging margin-based speaker embedding extractors by using the variational information bottleneck" [2024-06] [InterSpeech 2024] [paper]

• "Self-supervised learning of speech representations with Dutch archival data" [2025-07] [InterSpeech 2025] [paper]

• "R2S: Real-to-Synthetic Representation Learning for Training Speech Recognition Models on Synthetic Data" [2025-09] [InterSpeech 2025] [paper]

• "SiamCTC: Learning Speech Representations through Monotonic Temporal Alignment" [2025-09] [InterSpeech 2025] [paper]

• "Towards Classification of Typical and Atypical Disfluencies: A Self Supervised Representation Approach" [2025-09] [InterSpeech 2025] [paper]

4.3 Embedding Analysis

Representation Properties

• "Evaluating context-invariance in unsupervised speech representations" [2022-10] [InterSpeech 2023] [paper]

• "Perceptual Analysis of Speaker Embeddings for Voice Discrimination between Machine And Human Listening" [2023-01] [ICASSP 2023] [paper]

• "Analyzing Acoustic Word Embeddings from Pre-trained Self-supervised Models" [2023-01] [ICASSP 2023] [paper]

• "TRUST-SER: On The Trustworthiness Of Fine-Tuning Pre-Trained Speech Embeddings For Speech Emotion Recognition" [2023-05] [ICASSP 2024] [paper]

• "An Information-Theoretic Analysis of Self-supervised Discrete Representations of Speech" [2023-06] [InterSpeech 2023] [paper]

• "Investigating wav2vec2 context representations and the effects of fine-tuning, a case-study of a Finnish model" [2023-03] [InterSpeech 2023] [paper]

• "On the (In)Efficiency of Acoustic Feature Extractors for Self-Supervised Speech Representation Learning" [2023-08] [InterSpeech 2023] [paper]

• "On The Choice of the Optimal Temporal Support for Audio Classification with Pre-Trained Embeddings" [2023-12] [ICASSP 2024] [paper]

• "A Closer Look at Wav2vec2 Embeddings for On-Device Single-Channel Speech Enhancement" [2024-03] [ICASSP 2024] [paper]

• "Following the Embedding: Identifying Transition Phenomena in Wav2vec 2.0 Representations of Speech Audio" [2024-03] [ICASSP 2024] [paper]

• "Searching for Structure: Appraising the Organisation of Speech Features in wav2vec 2.0 Embeddings" [2024-05] [InterSpeech 2024] [paper]

• "Wav2vec 2.0 Embeddings Are No Swiss Army Knife -- A Case Study for Multiple Sclerosis" [2024-05] [InterSpeech 2024] [paper]

• "Self-Supervised Speech Representations are More Phonetic than Semantic" [2024-06] [InterSpeech 2024] [paper]

• "On the Encoding of Gender in Transformer-based ASR Representations" [2024-06] [InterSpeech 2024] [paper]

• "Orthogonality and isotropy of speaker and phonetic information in self-supervised speech representations" [2024-06] [InterSpeech 2024] [paper]

• "Investigating the Sensitivity of Pre-trained Audio Embeddings to Common Effects" [2025-01] [ICASSP 2025] [paper]

• "Evaluating the Effectiveness of Pre-Trained Audio Embeddings for Classification of Parkinson's Disease Speech Data" [2025-06] [InterSpeech 2025] [paper]

• "Acoustic Representation and Realization of Weak Elements Subcategories: In the Case of Tianjin Mandarin" [2025-08] [InterSpeech 2025] [paper]

• "A Study of Speech Embedding Similarities Between Australian Aboriginal and High-Resource Languages" [2025-09] [InterSpeech 2025] [paper]

• "Evaluating Deep Speaker Embedding Robustness to Domain, Sampling Rate, and Codec Variations" [2025-09] [InterSpeech 2025] [paper]

Speaker Characteristics

• "Quantitative Evidence on Overlooked Aspects of Enrollment Speaker Embeddings for Target Speaker Separation" [2022-10] [ICASSP 2023] [paper]

• "Speaker Embeddings as Individuality Proxy for Voice Stress Detection" [2023-06] [InterSpeech 2023] [paper]

• "Speaker Verification Across Ages: Investigating Deep Speaker Embedding Sensitivity to Age Mismatch in Enrollment and Test Speech" [2023-06] [InterSpeech 2023] [paper]

• "Behavioral Analysis of Pathological Speaker Embeddings of Patients During Oncological Treatment of Oral Cancer" [2023-07] [InterSpeech 2023] [paper]

• "Controllable Generation of Artificial Speaker Embeddings through Discovery of Principal Directions" [2023-10] [InterSpeech 2023] [paper]

• "Geodesic Interpolation of Frame-Wise Speaker Embeddings for the Diarization of Meeting Scenarios" [2024-01] [ICASSP 2024] [paper]

• "A Study on Graph Embedding for Speaker Recognition" [2024-03] [ICASSP 2024] [paper]

• "Spoofed Speech Detection with a Focus on Speaker Embedding" [2024-05] [InterSpeech 2024] [paper]

• "The reasonable effectiveness of speaker embeddings for violence detection" [2024-06] [InterSpeech 2024] [paper]

• "Gradual modeling of the Lombard effect by modifying speaker embeddings from a Text-To-Speech model" [2025-08] [InterSpeech 2025] [paper]

Benchmarking & Evaluating Extractors

• "In search of strong embedding extractors for speaker diarisation" [2022-10] [ICASSP 2023] [paper]

• "A Reality Check and A Practical Baseline for Semantic Speech Embedding" [2023-01] [ICASSP 2023] [paper]

• "Speech Self-Supervised Representation Benchmarking: Are We Doing it Right?" [2023-06] [InterSpeech 2023] [paper]

• "On the Usefulness of Speaker Embeddings for Speaker Retrieval in the Wild: A Comparative Study of x-vector and ECAPA-TDNN Models" [2024-07] [InterSpeech 2024] [paper]

• "Gender Representation in TV and Radio: Automatic Information Extraction methods versus Manual Analyses" [2024-06] [InterSpeech 2024] [paper]

• "Rethinking Leveraging Pre-Trained Multi-Layer Representations for Speaker Verification" [2025-09] [InterSpeech 2025] [paper]

Interpretability

• "Learning Interpretable Low-dimensional Representation via Physical Symmetry" [2023-02] [NeurIPS 2023] [paper]

• "Similar Hierarchical Representation of Speech and Other Complex Sounds In the Brain and Deep Residual Networks: An MEG Study" [2023-08] [InterSpeech 2023] [paper]

• "What do self-supervised speech representations encode? An analysis of languages, varieties, speaking styles and speakers" [2023-08] [InterSpeech 2023] [paper]

• "What Do Language Models Hear? Probing for Auditory Representations in Language Models" [2024-02] [ACL 2024] [paper]

• "From Sound to Meaning in the Auditory Cortex: A Neuronal Representation and Classification Analysis" [2024-05] [InterSpeech 2024] [paper]

• "XANE: eXplainable Acoustic Neural Embeddings" [2024-06] [InterSpeech 2024] [paper]

• "Form and Function in Prosodic Representation: In the Case of 'ma' in Tianjin Mandarin" [2024-09] [InterSpeech 2024] [paper]

Cross-Domain Generalization

• "Can Self-Supervised Neural Representations Pre-Trained on Human Speech distinguish Animal Callers?" [2023-05] [InterSpeech 2023] [paper]

• "On the Benefits of Self-supervised Learned Speech Representations for Predicting Human Phonetic Misperceptions" [2023-05] [InterSpeech 2023] [paper]

• "Towards hate speech detection in low-resource languages: Comparing ASR to acoustic word embeddings on Wolof and Swahili" [2023-06] [InterSpeech 2023] [paper]

• "Investigation of Layer-Wise Speech Representations in Self-Supervised Learning Models: A Cross-Lingual Study in Detecting Depression" [2024-05] [InterSpeech 2024] [paper]

• "Self-supervised Speech Representations Still Struggle with African American Vernacular English" [2024-08] [InterSpeech 2024] [paper]

• "Exploring Self-Supervised Speech Representations for Cross-lingual Acoustic-to-Articulatory Inversion" [2024-09] [InterSpeech 2024] [paper]

• "Gender and Language Identification in Multilingual Models of Speech: Exploring the Genericity and Robustness of Speech Representations" [2024-09] [InterSpeech 2024] [paper]

• "Representation of Perceived Prosodic Similarity of Conversational Feedback" [2025-05] [InterSpeech 2025] [paper]

• "Recreating Neural Activity During Speech Production with Language and Speech Model Embeddings" [2025-05] [InterSpeech 2025] [paper]

• "Dirichlet process mixture model based on topologically augmented signal representation for clustering infant vocalizations" [2024-07] [InterSpeech 2024] [paper]

4.4 Benchmarks & Toolkits

• "Wespeaker: A Research and Production Oriented Speaker Embedding Learning Toolkit" [2022-10] [ICASSP 2023] [paper]

• "MARBLE: Music Audio Representation Benchmark for Universal Evaluation" [2023-06] [NeurIPS 2023] [paper]

• "ESPnet-SPK: full pipeline speaker embedding toolkit with reproducible recipes, self-supervised front-ends, and off-the-shelf models" [2024-01] [InterSpeech 2024] [paper]

4.5 Embedding Applications

Speaker-Related Application

• "Advancing the Dimensionality Reduction of Speaker Embeddings for Speaker Diarisation: Disentangling Noise and Informing Speech Activity" [2021-10] [ICASSP 2023] [paper]

• "Exploiting Speaker Embeddings for Improved Microphone Clustering and Speech Separation in ad-hoc Microphone Arrays" [2023-03] [ICASSP 2023] [paper]

• "Towards Single Integrated Spoofing-aware Speaker Verification Embeddings" [2023-05] [InterSpeech 2023] [paper]

• "A Teacher-Student Approach for Extracting Informative Speaker Embeddings From Speech Mixtures" [2023-06] [InterSpeech 2023] [paper]

• "Improving End-to-End Neural Diarization Using Conversational Summary Representations" [2023-06] [InterSpeech 2023] [paper]

• "SEF-Net: Speaker Embedding Free Target Speaker Extraction Network" [2023-07] [InterSpeech 2023] [paper]

• "Real-Time Personalised Speech Enhancement Transformers with Dynamic Cross-attended Speaker Representations" [2023-08] [InterSpeech 2023] [paper]

• "SEF-VC: Speaker Embedding Free Zero-Shot Voice Conversion with Cross Attention" [2023-12] [ICASSP 2024] [paper]

• "Neural Speaker Diarization Using Memory-Aware Multi-Speaker Embedding with Sequence-to-Sequence Architecture" [2024-01] [ICASSP 2024] [paper]

• "Speakers Unembedded: Embedding-free Approach to Long-form Neural Diarization" [2024-05] [InterSpeech 2024] [paper]

• "Efficient Speaker Embedding Extraction Using a Twofold Sliding Window Algorithm for Speaker Diarization" [2024-05] [InterSpeech 2024] [paper]

• "Fully Few-shot Class-incremental Audio Classification Using Expandable Dual-embedding Extractor" [2024-06] [InterSpeech 2024] [paper]

• "Personalized Speech Enhancement Without a Separate Speaker Embedding Model" [2024-06] [InterSpeech 2024] [paper]

• "Audio Fingerprinting with Holographic Reduced Representations" [2024-06] [InterSpeech 2024] [paper]

• "Specializing Self-Supervised Speech Representations for Speaker Segmentation" [2024-09] [InterSpeech 2024] [paper]

• "Leveraging Boolean Directivity Embedding for Binaural Target Speaker Extraction" [2025-07] [ICASSP 2025] [paper]

• "Spatio-Spectral Diarization of Meetings by Combining TDOA-based Segmentation and Speaker Embedding-based Clustering" [2025-07] [InterSpeech 2025] [paper]

• "A Siamese Network-Based Framework for Voice Mimicry Proficiency Assessment Using X-Vector Embeddings" [2025-08] [InterSpeech 2025] [paper]

• "Bridging Speech and Singing: Multi-stage Speech-Prompted Singing Voice Conversion with Speaker Embedding Adaptation" [2025-08] [InterSpeech 2025] [paper]

Speech Recognition & Transcription

• "Multi-Lingual Pronunciation Assessment with Unified Phoneme Set and Language-Specific Embeddings" [2023-01] [ICASSP 2023] [paper]

• "Context-Aware end-to-end ASR Using Self-Attentive Embedding and Tensor Fusion" [2023-01] [ICASSP 2023] [paper]

• "Improvements to Embedding-Matching Acoustic-to-Word ASR Using Multiple-Hypothesis Pronunciation-Based Embeddings" [2023-01] [ICASSP 2023] [paper]

• "Self-supervised Learning Representation based Accent Recognition with Persistent Accent Memory" [2023-02] [InterSpeech 2023] [paper]

• "Text-only Domain Adaptation using Unified Speech-Text Representation in Transducer" [2023-06] [InterSpeech 2023] [paper]

• "TokenSplit: Using Discrete Speech Representations for Direct, Refined, and Transcript-Conditioned Speech Separation and Recognition" [2023-08] [InterSpeech 2023] [paper]

• "Dual Audio Encoders Based Mandarin Prosodic Boundary Prediction by Using Multi-Granularity Prosodic Representations" [2023-08] [InterSpeech 2023] [paper]

• "Transducers with Pronunciation-Aware Embeddings for Automatic Speech Recognition" [2024-01] [ICASSP 2024] [paper]

• "CIF-RNNT: Streaming ASR Via Acoustic Word Embeddings with Continuous Integrate-and-Fire and RNN-Transducers" [2024-01] [ICASSP 2024] [paper]

• "Codec-ASR: Training Performant Automatic Speech Recognition Systems with Discrete Speech Representations" [2024-05] [InterSpeech 2024] [paper]

• "Dysarthric Speech Recognition Using Curriculum Learning and Articulatory Feature Embedding" [2024-05] [InterSpeech 2024] [paper]

• "CTC-aligned Audio-Text Embedding for Streaming Open-vocabulary Keyword Spotting" [2024-06] [InterSpeech 2024] [paper]

• "Enhancing Multilingual ASR for Unseen Languages via Language Embedding Modeling" [2024-12] [ICASSP 2025] [paper]

Speech Emotion, Paralinguistic, Health & Cognitive Applications

• "Efficient Speech Quality Assessment Using Self-Supervised Framewise Embeddings" [2022-11] [ICASSP 2023] [paper]

• "Understanding Spoken Language Development of Children with ASD Using Pre-trained Speech Embeddings" [2023-05] [InterSpeech 2023] [paper]

• "Robust Self Supervised Speech Embeddings for Child-Adult Classification in Interactions involving Children with Autism" [2023-07] [InterSpeech 2023] [paper]

• "Classification of Vocal Intensity Category from Speech using the Wav2vec2 and Whisper Embeddings" [2023-08] [InterSpeech 2023] [paper]

• "AsthmaSCELNet: A Lightweight Supervised Contrastive Embedding Learning Framework for Asthma Classification Using Lung Sounds" [2023-08] [InterSpeech 2023] [paper]

• "A Compressed Synthetic Speech Detection Method with Compression Feature Embedding" [2023-08] [InterSpeech 2023] [paper]

• "Classifying depression symptom severity: Assessment of speech representations in personalized and generalized machine learning models." [2023-08] [InterSpeech 2023] [paper]

• "Automated Multiple Sclerosis Screening Based on Encoded Speech Representations" [2023-08] [InterSpeech 2023] [paper]

• "Obstructive Sleep Apnea Detection using Pre-trained Speech Representations" [2023-08] [InterSpeech 2023] [paper]

• "Enhancing Child Vocalization Classification with Phonetically-Tuned Embeddings for Assisting Autism Diagnosis" [2023-09] [InterSpeech 2024] [paper]

• "Fusing Multi-Level Features from Audio and Contextual Sentence Embedding from Text for Interview-Based Depression Detection" [2024-01] [ICASSP 2024] [paper]

• "Are Paralinguistic Representations all that is needed for Speech Emotion Recognition?" [2024-02] [InterSpeech 2024] [paper]

• "Whister: Using Whisper’s representations for Stuttering detection" [2024-05] [InterSpeech 2024] [paper]

• "Automatic Assessment of Speech Production Skills for Children with Cochlear Implants Using Wav2Vec2.0 Acoustic Embeddings" [2024-05] [InterSpeech 2024] [paper]

• "Automatic Classification of News Subjects in Broadcast News: Application to a Gender Bias Representation Analysis" [2024-05] [InterSpeech 2024] [paper]

• "Self-Supervised Embeddings for Detecting Individual Symptoms of Depression" [2024-06] [InterSpeech 2024] [paper]

• "Developing vocal system impaired patient-aimed voice quality assessment approach using ASR representation-included multiple features" [2024-08] [InterSpeech 2024] [paper]

• "Leveraging Universal Speech Representations for Detecting and Assessing the Severity of Mild Cognitive Impairment Across Languages" [2024-09] [InterSpeech 2024] [paper]

• "Multimodal Fusion of Music Theory-Inspired and Self-Supervised Representations for Improved Emotion Recognition" [2024-09] [InterSpeech 2024] [paper]

• "Multimodal Emotion Diarization: Frame-Wise Integration of Text and Audio Representations" [2025-08] [InterSpeech 2025] [paper]

• "Advancing Emotion Recognition via Ensemble Learning: Integrating Speech, Context, and Text Representations" [2025-09] [InterSpeech 2025] [paper]

• "Interactive Fusion of Multi-View Speech Embeddings via Pretrained Large-Scale Speech Models for Speech Emotional Attribute Prediction in Naturalistic Conditions" [2025-09] [InterSpeech 2025] [paper]

• "Voice-Based Dysphagia Detection: Leveraging Self-Supervised Speech Representation" [2025-09] [InterSpeech 2025] [paper]

Text-To-Speech

• "Exploiting Emotion Information in Speaker Embeddings for Expressive Text-to-Speech" [2023-08] [InterSpeech 2023] [paper]

• "SALTTS: Leveraging Self-Supervised Speech Representations for improved Text-to-Speech Synthesis" [2023-08] [InterSpeech 2023] [paper]

• "Accent Conversion with Articulatory Representations" [2024-06] [InterSpeech 2024] [paper]

• "Enhancing Multilingual TTS with Voice Conversion Based Data Augmentation and Posterior Embedding" [2024-07] [ICASSP 2024] [paper]

Spoofing & Security

• "Learning A Self-Supervised Domain-Invariant Feature Representation for Generalized Audio Deepfake Detection" [2023-08] [InterSpeech 2023] [paper]

• "An Efficient Temporary Deepfake Location Approach Based Embeddings for Partially Spoofed Audio Detection" [2023-09] [ICASSP 2024] [paper]

• "Interpretable Temporal Class Activation Representation for Audio Spoofing Detection" [2024-06] [InterSpeech 2024] [paper]

• "Attentive Merging of Hidden Embeddings from Pre-trained Speech Model for Anti-spoofing Detection" [2024-06] [InterSpeech 2024] [paper]

• "Towards generalisable and calibrated audio deepfake detection with self-supervised representations" [2024-09] [InterSpeech 2024] [paper]

• "An Explainable Probabilistic Attribute Embedding Approach for Spoofed Speech Characterization" [2024-09] [ICASSP 2025] [paper]

• "Exploring Self-supervised Embeddings and Synthetic Data Augmentation for Robust Audio Deepfake Detection" [2024-09] [InterSpeech 2024] [paper]

• "SpeechForensics: Audio-Visual Speech Representation Learning for Face Forgery Detection" [2025-08] [NeurIPS 2024] [paper]

• "Generalizable Audio Spoofing Detection using Non-Semantic Representations" [2025-08] [InterSpeech 2025] [paper]

• "Enhancing Audio Deepfake Detection by Improving Representation Similarity of Bonafide Speech" [2025-08] [InterSpeech 2025] [paper]

Others

• "Feature Selection and Text Embedding for Detecting Dementia from Spontaneous Cantonese" [2023-01] [ICASSP 2023] [paper]

• "Fully Unsupervised Topic Clustering of Unlabelled Spoken Audio Using Self-Supervised Representation Learning and Topic Model" [2023-03] [ICASSP 2023] [paper]

• "Understanding Disrupted Sentences Using Underspecified Abstract Meaning Representation" [2023-06] [InterSpeech 2023] [paper]

• "End to End Spoken Language Diarization with Wav2vec Embeddings" [2023-08] [InterSpeech 2023] [paper]

• "Flexible Keyword Spotting Based on Homogeneous Audio-Text Embedding" [2023-08] [ICASSP 2024] [paper]

• "Joint Prediction of Audio Event and Annoyance Rating in an Urban Soundscape by Hierarchical Graph Representation Learning" [2023-08] [InterSpeech 2023] [paper]

• "Enhanced Embeddings in Zero-Shot Learning for Environmental Audio" [2023-08] [ICASSP 2023] [paper]

• "Improving Audio Captioning Models with Fine-Grained Audio Features, Text Embedding Supervision, and LLM Mix-Up Augmentation" [2023-09] [ICASSP 2024] [paper]

• "A Deep Representation Learning-Based Speech Enhancement Method Using Complex Convolution Recurrent Variational Autoencoder" [2023-12] [ICASSP 2024] [paper]

• "Similar but Faster: Manipulation of Tempo in Music Audio Embeddings for Tempo Prediction and Search" [2024-01] [ICASSP 2024] [paper]

• "Improving Oral Reading Fluency Assessment Through Sub-Sequence Matching of Acoustic Word Embeddings" [2024-01] [ICASSP 2024] [paper]

• "Ainur: Harmonizing Speed and Quality in Deep Music Generation Through Lyrics-Audio Embeddings" [2024-01] [ICASSP 2024] [paper]

• "Sound of Vision: Audio Generation from Visual Text Embedding through Training Domain Discriminator" [2024-05] [InterSpeech 2024] [paper]

• "CALL system using pitch-accent feature representations reflecting listeners’ subjective adequacy" [2024-05] [InterSpeech 2024] [paper]

• "RevRIR: Joint Reverberant Speech and Room Impulse Response Embedding using Contrastive Learning with Application to Room Shape Classification" [2024-06] [InterSpeech 2024] [paper]

• "Joint Learning of Context and Feedback Embeddings in Spoken Dialogue" [2024-06] [InterSpeech 2024] [paper]

• "Multimodal Representation Loss Between Timed Text and Audio for Regularized Speech Separation" [2024-06] [InterSpeech 2024] [paper]

• "Text2FX: Harnessing CLAP Embeddings for Text-Guided Audio Effects" [2024-09] [ICASSP 2025] [paper]

• "Zero-shot Musical Stem Retrieval with Joint-Embedding Predictive Architectures" [2024-11] [ICASSP 2025] [paper]

• "Music2Latent2: Audio Compression with Summary Embeddings and Autoregressive Decoding" [2025-01] [ICASSP 2025] [paper]

• "Learning Musical Representations for Music Performance Question Answering" [2025-02] [EMNLP 2024 Findings] [paper]

• "Discrete Audio Representations for Automated Audio Captioning" [2025-05] [InterSpeech 2025] [paper]

• "CLAP-ART: Automated Audio Captioning with Semantic-rich Audio Representation Tokenizer" [2025-06] [InterSpeech 2025] [paper]

• "Efficient Speech Enhancement via Embeddings from Pre-trained Generative Audioencoders" [2025-06] [InterSpeech 2025] [paper]

• "Fully Few-shot Class-incremental Audio Classification Using Multi-level Embedding Extractor and Ridge Regression Classifier" [2025-06] [InterSpeech 2025] [paper]

• "Listen through the Sound: Generative Speech Restoration Leveraging Acoustic Context Representation" [2025-08] [InterSpeech 2025] [paper]

• "Dog2vec: Self-Supervised Pre-Training for Canine Vocal Representation" [2025-08] [InterSpeech 2025] [paper]

• "Simple and Effective Content Encoder for Singing Voice Conversion via SSL-Embedding Dimension Reduction" [2025-08] [InterSpeech 2025] [paper]

• "GoP2Vec: A few shot learning for pronunciation assessment with goodness of pronunciation (GoP) based representations from an i-vector framework and augmentation" [2025-08] [InterSpeech 2025] [paper]

• "FUSE-MOS: Fusion of Speech Embeddings for MOS Prediction with Uncertainty Quantification" [2025-08] [InterSpeech 2025] [paper]

• "Causal Speech Enhancement Based on a Two-Branch Nested U-Net Architecture Using Self-Supervised Speech Embeddings" [2025-08] [ICASSP 2025] [paper]

5. Graph Embedding

5.1 Node Embedding

• "Deepwalk: Online learning of social representations" [2014-03] [KDD 2014] [paper]

• "Line: Large-scale information network embedding" [2015-03] [WWW 2015] [paper]

• "node2vec: Scalable feature learning for networks" [2016-07] [KDD 2016] [paper]

• "Asymmetric transitivity preserving graph embedding" [2016-08] [KDD 2016] [paper]

• "Semi-Supervised Classification with Graph Convolutional Networks" [2016-09] [ICLR 2017] [paper]

• "Inductive representation learning on large graphs" [2017-06] [NeurIPS 2017] [paper]

• "metapath2vec: Scalable representation learning for heterogeneous networks" [2017-08] [KDD 2017] [paper]

• "Graph attention networks" [2017-10] [ICLR 2018] [paper]

• "How powerful are graph neural networks?" [2018-10] [ICLR 2019] [paper]

• "Relational graph attention networks" [2019-04] [KDD 2020] [paper]

• "Do transformers really perform badly for graph representation?" [2021-06] [NeurIPS 2021] [paper]

• "Nodepiece: Compositional and parameter-efficient representations of large knowledge graphs" [2021-06] [ICLR 2022] [paper]

• "Sign and Basis Invariant Networks for Spectral Graph Representation Learning" [2022-02] [ICLR 2023] [paper]

• "Translating Subgraphs to Nodes Makes Simple GNNs Strong and Efficient for Subgraph Representation Learning" [2022-04] [ICML 2024] [paper]

• "Empowering Graph Representation Learning with Test-Time Graph Transformation" [2022-10] [ICLR 2023] [paper]

• "DyG2Vec: Efficient Representation Learning for Dynamic Graphs" [2022-10] [TMLR 2024] [paper]

• "Learning Fair Graph Representations via Automated Data Augmentations" [2023-02] [ICLR 2023] [paper]

• "Chasing All-Round Graph Representation Robustness: Model, Training, and Optimization" [2023-02] [ICLR 2023] [paper]

• "Spacetime Representation Learning" [2023-02] [ICLR 2023] [paper]

• "Towards Better Graph Representation Learning with Parameterized Decomposition & Filtering" [2023-05] [ICML 2023] [paper]

• "Fisher Information Embedding for Node and Graph Learning" [2023-05] [ICML 2023] [paper]

• "Tractable Probabilistic Graph Representation Learning with Graph-Induced Sum-Product Networks" [2023-05] [ICLR 2024] [paper]

• "Seq-HGNN: Learning Sequential Node Representation on Heterogeneous Graph" [2023-05] [SIGIR 2023] [paper]

• "Node Embedding from Neural Hamiltonian Orbits in Graph Neural Networks" [2023-05] [ICML 2023] [paper]

• "Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning" [2023-05] [ICLR 2024] [paper]

• "SGFormer: Simplifying and Empowering Transformers for Large-Graph Representations" [2023-06] [NeurIPS 2023] [paper]

• "Directional diffusion models for graph representation learning" [2023-06] [NeurIPS 2023] [paper]

• "When Sparsity Meets Contrastive Models: Less Graph Data Can Bring Better Class-Balanced Representations" [2023-06] [ICML 2023] [paper]

• "Disentangled Multiplex Graph Representation Learning" [2023-06] [ICML 2023] [paper]

• "VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs" [2023-08] [ICLR 2024] [paper]

• "Graph-enhanced Optimizers for Structure-aware Recommendation Embedding Evolution" [2023-09] [NeurIPS 2024] [paper]

• "LD2: Scalable Heterophilous Graph Neural Network with Decoupled Embeddings" [2023-09] [NeurIPS 2023] [paper]

• "WalkLM: A Uniform Language Model Fine-tuning Framework for Attributed Graph Embedding" [2023-09] [NeurIPS 2023] [paper]

• "FiGURe: Simple and Efficient Unsupervised Node Representations with Filter Augmentations" [2023-10] [NeurIPS 2023] [paper]

• "GRENADE: Graph-Centric Language Model for Self-Supervised Representation Learning on Text-Attributed Graphs" [2023-10] [EMNLP 2023 Findings] [paper]

• "Community Detection Guarantees using Embeddings Learned by Node2Vec" [2023-10] [NeurIPS 2024] [paper]

• "Zero-shot Node Classification with Graph Contrastive Embedding Network" [2023-10] [TMLR 2023] [paper]

• "Content- and Topology-Aware Representation Learning for Scientific Multi-Literature" [2023-12] [EMNLP 2023] [paper]

• "Recurrent Distance Filtering for Graph Representation Learning" [2023-12] [ICML 2024] [paper]

• "HypeBoy: Generative Self-Supervised Representation Learning on Hypergraphs" [2024-01] [ICLR 2024] [paper]

• "UNR-Explainer: Counterfactual Explanations for Unsupervised Node Representation Learning Models" [2024-01] [ICLR 2024] [paper]

• "Node2ket: Efficient High-Dimensional Network Embedding in Quantum Hilbert Space" [2024-01] [ICLR 2024] [paper]

• "Learning Invariant Representations of Graph Neural Networks via Cluster Generalization" [2024-03] [NeurIPS 2023] [paper]

• "High-Frequency-aware Hierarchical Contrastive Selective Coding for Representation Learning on Text Attributed Graphs" [2024-04] [WWW 2024] [paper]

• "Node Identifiers: Compact, Discrete Representations for Efficient Graph Learning" [2024-05] [ICLR 2025] [paper]

• "Enhancing Size Generalization in Graph Neural Networks through Disentangled Representation Learning" [2024-06] [ICML 2024] [paper]

• "Learning Divergence Fields for Shift-Robust Graph Representations" [2024-06] [ICML 2024] [paper]

• "DUPLEX: Dual GAT for Complex Embedding of Directed Graphs" [2024-06] [ICML 2024] [paper]

• "Explaining Node Embeddings" [2024-06] [TMLR 2025] [paper]

• "Leveraging Contrastive Learning for Enhanced Node Representations in Tokenized Graph Transformers" [2024-06] [NeurIPS 2024] [paper]

• "Non-Euclidean Mixture Model for Social Network Embedding" [2024-09] [NeurIPS 2024] [paper]

• "Learning Representations for Hierarchies with Minimal Support" [2024-09] [NeurIPS 2024] [paper]

• "Disentangled and Self-Explainable Node Representation Learning" [2024-10] [TMLR 2025] [paper]

• "LASE: Learned Adjacency Spectral Embeddings" [2024-12] [TMLR 2025] [paper]

• "Generalizable Spectral Embedding with an Application to UMAP" [2025-01] [TMLR 2025] [paper]

• "Holographic Node Representations: Pre-training Task-Agnostic Node Embeddings" [2025-01] [ICLR 2025] [paper]

• "Disobeying Directions: Switching Random Walk Filters for Unsupervised Node Embedding Learning on Directed Graphs" [2025-01] [TMLR 2025] [paper]

• "Genetic-Evolutionary Graph Neural Networks: A Paradigm for Improved Graph Representation Learning" [2025-02] [TMLR 2025] [paper]

• "Balancing Graph Embedding Smoothness in Self-supervised Learning via Information-Theoretic Decomposition" [2025-04] [WWW 2025] [paper]

• "GPEN: Global Position Encoding Network for Enhanced Subgraph Representation Learning" [2025-05] [ICML 2025] [paper]

• "Primphormer: Efficient Graph Transformers with Primal Representations" [2025-05] [ICML 2025] [paper]

• "SDMG: Smoothing Your Diffusion Models for Powerful Graph Representation Learning" [2025-05] [ICML 2025] [paper]

• "Stable Fair Graph Representation Learning with Lipschitz Constraint" [2025-05] [ICML 2025] [paper]

• "iN2V: Bringing Transductive Node Embeddings to Inductive Graphs" [2025-06] [ICML 2025] [paper]

• "Full-Rank Unsupervised Node Embeddings for Directed Graphs via Message Aggregation" [2025-06] [TMLR 2025] [paper]

• "Node2binary: Compact Graph Node Embeddings using Binary Vectors" [2025-06] [WWW 2025] [paper]

5.2 Graph Embedding

• "Evaluating Self-Supervised Learning for Molecular Graph Embeddings" [2022-06] [NeurIPS 2023] [paper]

• "Tight and fast generalization error bound of graph embedding in metric space" [2023-05] [ICML 2023] [paper]

• "Expectation-Complete Graph Representations with Homomorphisms" [2023-06] [ICML 2023] [paper]

• "PlanE: Representation Learning over Planar Graphs" [2023-07] [NeurIPS 2023] [paper]

• "Rethinking the Power of Graph Canonization in Graph Representation Learning with Stability" [2023-09] [ICLR 2024] [paper]

• "Graph-level Representation Learning with Joint-Embedding Predictive Architectures" [2023-09] [TMLR 2025] [paper]

• "Lovász Principle for Unsupervised Graph Representation Learning" [2023-09] [NeurIPS 2023] [paper]

• "Laplacian Canonization: A Minimalist Approach to Sign and Basis Invariant Spectral Embedding" [2023-10] [NeurIPS 2023] [paper]

• "Normed Spaces for Graph Embedding" [2023-12] [ICLR 2025] [paper]

• "A Simple and Scalable Representation for Graph Generation" [2023-12] [ICLR 2024] [paper]

• "Weisfeiler and Leman Go Loopy: A New Hierarchy for Graph Representational Learning" [2024-03] [NeurIPS 2024] [paper]

• "HC-GAE: The Hierarchical Cluster-based Graph Auto-Encoder for Graph Representation Learning" [2024-05] [NeurIPS 2024] [paper]

• "Learning Graph Representation via Graph Entropy Maximization" [2024-07] [ICML 2024] [paper]

• "Neural Spacetimes for DAG Representation Learning" [2024-08] [ICLR 2025] [paper]

• "LLMs as Zero-shot Graph Learners: Alignment of GNN Representations with LLM Token Embeddings" [2024-08] [NeurIPS 2024] [paper]

• "Exploitation of a Latent Mechanism in Graph Contrastive Learning: Representation Scattering" [2024-09] [NeurIPS 2024] [paper]

• "Exploring Consistency in Graph Representations: from Graph Kernels to Graph Neural Networks" [2024-10] [NeurIPS 2024] [paper]

• "ICLR: In-Context Learning of Representations" [2025-01] [ICLR 2025] [paper]

• "How Low Can You Go? Searching for the Intrinsic Dimensionality of Complex Networks using Metric Node Embeddings" [2025-01] [ICLR 2025] [paper]

• "Charting the Design Space of Neural Graph Representations for Subgraph Matching" [2025-01] [ICLR 2025] [paper]

• "A Hubness Perspective on Representation Learning for Graph-Based Multi-View Clustering" [2025-06] [CVPR 2025] [paper]

• "Heterogeneous Graph Embedding Made More Practical" [2025-07] [SIGIR 2025] [paper]

5.3 Edge Embedding

• "Edgeformers: Graph-Empowered Transformers for Representation Learning on Textual-Edge Networks" [2023-02] [ICLR 2023] [paper]

• "Towards characterizing the value of edge embeddings in Graph Neural Networks" [2024-10] [ICML 2025] [paper]

5.4 Knowledge Graph Embedding

• "Translating embeddings for modeling multi-relational data" [2013-12] [NeurIPS 2013] [paper]

• "Rotate: Knowledge graph embedding by relational rotation in complex space" [2019-02] [ICLR 2019] [paper]

• "Knowledge Hypergraph Embedding Meets Relational Algebra" [2021-02] [ICML 2023] [paper]

• "ExpressivE: A Spatio-Functional Embedding For Knowledge Graph Completion" [2022-06] [ICLR 2023] [paper]

• "RulE: Knowledge Graph Reasoning with Rule Embedding" [2022-10] [ACL 2024 Findings] [paper]

• "Wasserstein-Fisher-Rao Embedding: Logical Query Embeddings with Local Comparison and Global Transport" [2023-05] [ACL 2023 Findings] [paper]

• "Polar Ducks and Where to Find Them: Enhancing Entity Linking with Duck Typing and Polar Box Embeddings" [2023-05] [EMNLP 2023] [paper]

• "How to Turn Your Knowledge Graph Embeddings into Generative Models" [2023-05] [NeurIPS 2023] [paper]

• "InGram: Inductive Knowledge Graph Embedding via Relation Graphs" [2023-05] [ICML 2023] [paper]

• "Shrinking Embeddings for Hyper-Relational Knowledge Graphs" [2023-06] [ACL 2023] [paper]

• "What Makes Entities Similar? A Similarity Flooding Perspective for Multi-sourced Knowledge Graph Embeddings" [2023-06] [ICML 2023] [paper]

• "Knowledge Graph Embeddings using Neural Ito Process: From Multiple Walks to Stochastic Trajectories" [2023-07] [ACL 2023 Findings] [paper]

• "SConE: Simplified Cone Embeddings with Symbolic Operators for Complex Logical Queries" [2023-07] [ACL 2023 Findings] [paper]

• "Contrastive Learning with Generated Representations for Inductive Knowledge Graph Embedding" [2023-07] [ACL 2023 Findings] [paper]

• "Concept2Box: Joint Geometric Embeddings for Learning Two-View Knowledge Graphs" [2023-07] [ACL 2023 Findings] [paper]

• "Weighted Knowledge Graph Embedding" [2023-07] [SIGIR 2023] [paper]

• "Relation-aware Ensemble Learning for Knowledge Graph Embedding" [2023-10] [EMNLP 2023] [paper]

• "Solving Hard Analogy Questions with Relation Embedding Chains" [2023-10] [EMNLP 2023] [paper]

• "Are Embedded Potatoes Still Vegetables? On the Limitations of WordNet Embeddings for Lexical Semantics" [2023-12] [EMNLP 2023] [paper]

• "Block-Diagonal Orthogonal Relation and Matrix Entity for Knowledge Graph Embedding" [2024-01] [EMNLP 2024 Findings] [paper]

• "MQuinE: a Cure for “Z-paradox” in Knowledge Graph Embedding" [2024-02] [EMNLP 2024] [paper]

• "Dynamic Graph Representation with Knowledge-aware Attention for Histopathology Whole Slide Image Analysis" [2024-03] [CVPR 2024] [paper]

• "PAC-Bayesian Generalization Bounds for Knowledge Graph Representation Learning" [2024-05] [ICML 2024] [paper]

• "Generalizing Knowledge Graph Embedding with Universal Orthogonal Parameterization" [2024-05] [ICML 2024] [paper]

• "Multiple Heads are Better than One: Mixture of Modality Knowledge Experts for Entity Representation Learning" [2024-05] [ICLR 2025] [paper]

• "Bridging the Space Gap: Unifying Geometry Knowledge Graph Embedding with Optimal Transport" [2024-05] [WWW 2024] [paper]

• "SpeedE: Euclidean Geometric Knowledge Graph Embedding Strikes Back" [2024-06] [NAACL 2024 Findings] [paper]

• "Improving Multi-hop Logical Reasoning in Knowledge Graphs with Context-Aware Query Representation Learning" [2024-06] [ACL 2024 Findings] [paper]

• "Croppable Knowledge Graph Embedding" [2024-07] [ACL 2025] [paper]

• "Learning Low-dimensional Multi-domain Knowledge Graph Embedding via Dual Archimedean Spirals" [2024-08] [ACL 2024 Findings] [paper]

• "HyperCL: A Contrastive Learning Framework for Hyper-Relational Knowledge Graph Embedding with Hierarchical Ontology" [2024-08] [ACL 2024 Findings] [paper]

• "Enhancing Hyperbolic Knowledge Graph Embeddings via Lorentz Transformations" [2024-08] [ACL 2024 Findings] [paper]

• "Predictive Multiplicity of Knowledge Graph Embeddings in Link Prediction" [2024-08] [EMNLP 2024 Findings] [paper]

• "Conformalized Answer Set Prediction for Knowledge Graph Embedding" [2024-08] [NAACL 2025] [paper]

• "Clustering then Propagation: Select Better Anchors for Knowledge Graph Embedding" [2024-09] [NeurIPS 2024] [paper]

• "DECRL: A Deep Evolutionary Clustering Jointed Temporal Knowledge Graph Representation Learning Approach" [2024-10] [NeurIPS 2024] [paper]

• "Joint Pre-Encoding Representation and Structure Embedding for Efficient and Low-Resource Knowledge Graph Completion" [2024-11] [EMNLP 2024] [paper]

• "Optimal Embedding Guided Negative Sample Generation for Knowledge Graph Link Prediction" [2025-04] [TMLR 2025] [paper]

• "A Mutual Information Perspective on Knowledge Graph Embedding" [2025-05] [ACL 2025] [paper]

• "Predicate-Conditional Conformalized Answer Sets for Knowledge Graph Embeddings" [2025-05] [ACL 2025 Findings] [paper]

• "RSCF: Relation-Semantics Consistent Filter for Entity Embedding of Knowledge Graph" [2025-05] [ACL 2025] [paper]

• "Structure Is All You Need: Structural Representation Learning on Hyper-Relational Knowledge Graphs" [2025-05] [ICML 2025] [paper]

• "From Knowledge Forgetting to Accumulation: Evolutionary Relation Path Passing for Lifelong Knowledge Graph Embedding" [2025-07] [SIGIR 2025] [paper]

• "Rethinking Continual Knowledge Graph Embedding: Benchmarks and Analysis" [2025-07] [SIGIR 2025] [paper]

6. Time Series Embedding

6.1 Foundation Models

• "Towards a General Time Series Forecasting Model with Unified Representation and Adaptive Transfer" [2024-05] [ICML 2025] [paper]

• "On the Regularization of Learnable Embeddings for Time Series Forecasting" [2025-02] [TMLR 2025] [paper]

• "Exploring Representations and Interventions in Time Series Foundation Models" [2025-06] [ICML 2025] [paper]

6.2 Model Architecture & Training Methods

• "SOM-CPC: Unsupervised Contrastive Learning with Self-Organizing Maps for Structured Representations of High-Rate Time Series" [2022-05] [ICML 2023] [paper]

• "Out-of-distribution Representation Learning for Time Series Classification" [2022-09] [ICLR 2023] [paper]

• "TEST: Text Prototype Aligned Embedding to Activate LLM's Ability for Time Series" [2023-08] [ICLR 2024] [paper]

• "T-Rep: Representation Learning for Time Series using Time-Embeddings" [2023-10] [ICLR 2024] [paper]

• "NuTime: Numerically Multi-Scaled Embedding for Large-Scale Time-Series Pretraining" [2023-10] [TMLR 2024] [paper]

• "Time Series Kernels based on Nonlinear Vector AutoRegressive Delay Embeddings" [2023-12] [NeurIPS 2023] [paper]

• "CaRiNG: Learning Temporal Causal Representation under Non-Invertible Generation Process" [2024-01] [ICML 2024] [paper]

• "TOTEM: TOkenized Time Series EMbeddings for General Time Series Analysis" [2024-02] [TMLR 2024] [paper]

• "Multi-Patch Prediction: Adapting Language Models for Time Series Representation Learning" [2024-03] [ICML 2024] [paper]

• "TSLANet: Rethinking Transformers for Time Series Representation Learning" [2024-04] [ICML 2024] [paper]

• "Segment, Shuffle, and Stitch: A Simple Layer for Improving Time-Series Representations" [2024-05] [NeurIPS 2024] [paper]

• "GAFormer: Enhancing Timeseries Transformers Through Group-Aware Embeddings" [2024-05] [ICLR 2024] [paper]

• "Disentangling Time Series Representations via Contrastive Independence-of-Support on l-Variational Inference" [2024-05] [ICLR 2024] [paper]

• "Nonlinear Sequence Embedding by Monotone Variational Inequality" [2024-06] [ICLR 2025] [paper]

• "MF-CLR: Multi-Frequency Contrastive Learning Representation for Time Series" [2024-07] [ICML 2024] [paper]

• "SigDiffusions: Score-Based Diffusion Models for Time Series via Log-Signature Embeddings" [2025-02] [ICLR 2025] [paper]

• "LETS-C: Leveraging Text Embedding for Time Series Classification" [2025-05] [ACL 2025] [paper]

• "TimeDART: A Diffusion Autoregressive Transformer for Self-Supervised Time Series Representation" [2025-06] [ICML 2025] [paper]

• "MERIT: Multi-Agent Collaboration for Unsupervised Time Series Representation Learning" [2025-07] [ACL 2025 Findings] [paper]

• "Time Series Representations with Hard-Coded Invariances" [2025-07] [ICML 2025] [paper]

• "Learning Time-Series Representations by Hierarchical Uniformity-Tolerance Latent Balancing" [2025-10] [TMLR 2025] [paper]

6.3 Temporal Knowledge Graph

• "ECOLA: Enhancing Temporal Knowledge Embeddings with Contextualized Language Representations" [2022-03] [ACL 2023 Findings] [paper]

• "TFLEX: Temporal Feature-Logic Embedding Framework for Complex Reasoning over Temporal Knowledge Graph" [2022-05] [NeurIPS 2023] [paper]

• "TeAST: Temporal Knowledge Graph Embedding via Archimedean Spiral Timeline" [2023-07] [ACL 2023] [paper]

• "Learning Joint Structural and Temporal Contextualized Knowledge Embeddings for Temporal Knowledge Graph Completion" [2023-07] [ACL 2023 Findings] [paper]

• "Noether Embedding: Efficient Learning of Temporal Regularities" [2023-12] [NeurIPS 2023] [paper]

• "Mitigating Heterogeneity among Factor Tensors via Lie Group Manifolds for Tensor Decomposition Based Temporal Knowledge Graph Embedding" [2025-02] [NAACL 2025] [paper]

6.4 Temporal Networks

• "Direct Embedding of Temporal Network Edges via Time-Decayed Line Graphs" [2022-09] [ICLR 2023] [paper]

• "HiT-MDP: Learning the SMDP option framework on MDPs with Hidden Temporal Embeddings" [2023-05] [ICLR 2023] [paper]