Awesome LLM Diversity

A curated collection of research papers exploring diversity in Large Language Model text generation. This repository tracks cutting-edge research on methods, evaluation, annalysis, and application. Research from all relative domains are welcome!

🤝 Contributing

We welcome contributions! If you know of important papers that should be included, please:

1. Fork this repository
2. Add the paper URL to the appropriate category
3. Submit a pull request

⭐ Support

If you find this collection useful, please consider starring, following for updates, and sharing with others!

🛠️ Maintenance

This repository is built and maintained using the automatic maintainer. New papers are added regularly after manual auditing to ensure comprehensive coverage of the field.

Methodology

Decoding

• Flaming-hot Initiation with Regular Execution Sampling for Large Language Models [paper] 2024-10
  Weizhe Chen, Zhicheng Zhang, Guanlin Liu, Renjie Zheng, Wenlei Shi, Chen Dun, Zheng Wu, Xing Jin, Lin Yan.

• PAD: Personalized Alignment of LLMs at Decoding-Time [paper] 2024-10
  Ruizhe Chen, Xiaotian Zhang, Meng Luo, Wenhao Chai, Zuozhu Liu. ICLR 2025.

  Keywords: Personalization.

• Chain-of-Thought Reasoning Without Prompting [paper] 2024-02
  Xuezhi Wang, Denny Zhou.

  Keywords: Reasoning, CoT.

• Diverse Beam Search: Decoding Diverse Solutions from Neural Sequence Models [paper] 2016-10
  Ashwin K Vijayakumar, Michael Cogswell, Ramprasath R. Selvaraju, Qing Sun, Stefan Lee, David Crandall, Dhruv Batra. AAAI 2018.

Finetuning

• Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time [paper] 2022-03
  Mitchell Wortsman, Gabriel Ilharco, Samir Yitzhak Gadre, Rebecca Roelofs, Raphael Gontijo-Lopes, Ari S. Morcos, Hongseok Namkoong, Ali Farhadi, Yair Carmon, Simon Kornblith, Ludwig Schmidt. ICML 2022.

• A Distributional Approach to Controlled Text Generation [paper] 2020-12
  Muhammad Khalifa, Hady Elsahar, Marc Dymetman. ICLR 2021.

Reinforcement Learning

• Creative Preference Optimization [paper] 2025-05
  Mete Ismayilzada, Antonio Laverghetta Jr., Simone A. Luchini, Reet Patel, Antoine Bosselut, Lonneke van der Plas, Roger Beaty.

• Modifying Large Language Model Post-Training for Diverse Creative Writing [paper] 2025-03
  John Joon Young Chung, Vishakh Padmakumar, Melissa Roemmele, Yuqian Sun, Max Kreminski.

• Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF [paper] 2023-12
  Anand Siththaranjan, Cassidy Laidlaw, Dylan Hadfield-Menell. ICLR 2024.

• Iteratively Learn Diverse Strategies with State Distance Information [paper] 2023-10
  Wei Fu, Weihua Du, Jingwei Li, Sunli Chen, Jingzhao Zhang, Yi Wu.

• Beyond Reverse KL: Generalizing Direct Preference Optimization with Diverse Divergence Constraints [paper] 2023-09
  Chaoqi Wang, Yibo Jiang, Chenghao Yang, Han Liu, Yuxin Chen.

• Rewarded soups: towards Pareto-optimal alignment by interpolating weights fine-tuned on diverse rewards [paper] 2023-06
  Alexandre Ramé, Guillaume Couairon, Mustafa Shukor, Corentin Dancette, Jean-Baptiste Gaya, Laure Soulier, Matthieu Cord.

• Aligning Language Models with Preferences through f-divergence Minimization [paper] 2023-02
  Dongyoung Go, Tomasz Korbak, Germán Kruszewski, Jos Rozen, Nahyeon Ryu, Marc Dymetman.

• Optimizing Temperature for Language Models with Multi-Sample Inference [paper] 2025-02
  Weihua Du, Yiming Yang, Sean Welleck.

  Keywords: Temperature.

• SimpleStrat: Diversifying Language Model Generation with Stratification [paper] 2024-10
  Justin Wong, Yury Orlovskiy, Michael Luo, Sanjit A. Seshia, Joseph E. Gonzalez.

• Improving Diversity of Commonsense Generation by Large Language Models via In-Context Learning [paper] 2024-04
  Tianhui Zhang, Bei Peng, Danushka Bollegala. EMNLP 2024.

• Forcing Diffuse Distributions out of Language Models [paper] 2024-04
  Yiming Zhang, Avi Schwarzschild, Nicholas Carlini, Zico Kolter, Daphne Ippolito.

  Keywords: Randomness.

• Partially Randomizing Transformer Weights for Dialogue Response Diversity [paper] 2023-11
  Jing Yang Lee, Kong Aik Lee, Woon-Seng Gan.

  Keywords: Framework.

• Improving Diversity of Demographic Representation in Large Language Models via Collective-Critiques and Self-Voting [paper] 2023-10
  Preethi Lahoti, Nicholas Blumm, Xiao Ma, Raghavendra Kotikalapudi, Sahitya Potluri, Qijun Tan, Hansa Srinivasan, Ben Packer, Ahmad Beirami, Alex Beutel, Jilin Chen. EMNLP 2023.

• Enhancing Large Language Models Against Inductive Instructions with Dual-critique Prompting [paper] 2023-05
  Rui Wang, Hongru Wang, Fei Mi, Yi Chen, Boyang Xue, Kam-Fai Wong, Ruifeng Xu.

• Diversify and Disambiguate: Learning From Underspecified Data [paper] 2022-02
  Yoonho Lee, Huaxiu Yao, Chelsea Finn. ICLR 2023.

Measurement and Analysis

• Base Models Beat Aligned Models at Randomness and Creativity [paper] 2025-04
  Peter West, Christopher Potts.

• NoveltyBench: Evaluating Language Models for Humanlike Diversity [paper] 2025-04
  Yiming Zhang, Harshita Diddee, Susan Holm, Hanchen Liu, Xinyue Liu, Vinay Samuel, Barry Wang, Daphne Ippolito.

  Keywords: Benchmark.

• (How) Can Transformers Predict Pseudo-Random Numbers? [paper] 2025-02
  Tao Tao, Darshil Doshi, Dayal Singh Kalra, Tianyu He, Maissam Barkeshli.

  Keywords: Randomness.

• Every Answer Matters: Evaluating Commonsense with Probabilistic Measures [paper] 2024-06
  Qi Cheng, Michael Boratko, Pranay Kumar Yelugam, Tim O'Gorman, Nalini Singh, Andrew McCallum, Xiang Lorraine Li. ACL 2024.

• What Evidence Do Language Models Find Convincing? [paper] 2024-02
  Alexander Wan, Eric Wallace, Dan Klein. ACL 2024.

• Exploring Precision and Recall to assess the quality and diversity of LLMs [paper] 2024-02
  Florian Le Bronnec, Alexandre Verine, Benjamin Negrevergne, Yann Chevaleyre, Alexandre Allauzen. ACL 2024.

• Measurement in the Age of LLMs: An Application to Ideological Scaling [paper] 2023-12
  Sean O'Hagan, Aaron Schein. NeurIPS 2023.

• The Curious Decline of Linguistic Diversity: Training Language Models on Synthetic Text [paper] 2023-11
  Yanzhu Guo, Guokan Shang, Michalis Vazirgiannis, Chloé Clavel. ACL 2024.

  Keywords: Data Synthesis.

• Understanding the Effects of RLHF on LLM Generalisation and Diversity [paper] 2023-10
  Robert Kirk, Ishita Mediratta, Christoforos Nalmpantis, Jelena Luketina, Eric Hambro, Edward Grefenstette, Roberta Raileanu.

• DyVal: Dynamic Evaluation of Large Language Models for Reasoning Tasks [paper] 2023-09
  Kaijie Zhu, Jiaao Chen, Jindong Wang, Neil Zhenqiang Gong, Diyi Yang, Xing Xie. ICLR 2024.

  Keywords: Reasoning.

• Art or Artifice? Large Language Models and the False Promise of Creativity [paper] 2023-09
  Tuhin Chakrabarty, Philippe Laban, Divyansh Agarwal, Smaranda Muresan, Chien-Sheng Wu. CHI 2024.

• Evaluating the Moral Beliefs Encoded in LLMs [paper] 2023-07
  Nino Scherrer, Claudia Shi, Amir Feder, David M. Blei.

• Towards Measuring the Representation of Subjective Global Opinions in Language Models [paper] 2023-06
  Esin Durmus, Karina Nguyen, Thomas I. Liao, Nicholas Schiefer, Amanda Askell, Anton Bakhtin, Carol Chen, Zac Hatfield-Dodds, Danny Hernandez, Nicholas Joseph, Liane Lovitt, Sam McCandlish, Orowa Sikder, Alex Tamkin, Janel Thamkul, Jared Kaplan, Jack Clark, Deep Ganguli.

  Keywords: Question Answering, Dataset.

• Generating with Confidence: Uncertainty Quantification for Black-box Large Language Models [paper] 2023-05
  Zhen Lin, Shubhendu Trivedi, Jimeng Sun.

• ChatGPT to Replace Crowdsourcing of Paraphrases for Intent Classification: Higher Diversity and Comparable Model Robustness [paper] 2023-05
  Jan Cegin, Jakub Simko, Peter Brusilovsky. EMNLP 2023.

• What Comes Next? Evaluating Uncertainty in Neural Text Generators Against Human Production Variability [paper] 2023-05
  Mario Giulianelli, Joris Baan, Wilker Aziz, Raquel Fernández, Barbara Plank. EMNLP 2023.

• Pragmatically Appropriate Diversity for Dialogue Evaluation [paper] 2023-04
  Katherine Stasaski, Marti A. Hearst.

• Language Model Crossover: Variation through Few-Shot Prompting [paper] 2023-02
  Elliot Meyerson, Mark J. Nelson, Herbie Bradley, Adam Gaier, Arash Moradi, Amy K. Hoover, Joel Lehman.

• Measuring and Improving Semantic Diversity of Dialogue Generation [paper] 2022-10
  Seungju Han, Beomsu Kim, Buru Chang.

• Semantic Diversity in Dialogue with Natural Language Inference [paper] 2022-05
  Katherine Stasaski, Marti A. Hearst. ACL 2022.

• Unifying Human and Statistical Evaluation for Natural Language Generation [paper] 2019-04
  Tatsunori B. Hashimoto, Hugh Zhang, Percy Liang.

Alignment

• SPARTA ALIGNMENT: Collectively Aligning Multiple Language Models through Combat [paper] 2025-06
  Yuru Jiang, Wenxuan Ding, Shangbin Feng, Greg Durrett, Yulia Tsvetkov.

• Preference Optimization with Multi-Sample Comparisons [paper] 2024-10
  Chaoqi Wang, Zhuokai Zhao, Chen Zhu, Karthik Abinav Sankararaman, Michal Valko, Xuefei Cao, Zhaorun Chen, Madian Khabsa, Yuxin Chen, Hao Ma, Sinong Wang.

• Can Language Models Reason about Individualistic Human Values and Preferences? [paper] 2024-10
  Liwei Jiang, Taylor Sorensen, Sydney Levine, Yejin Choi. ACL 2025.

• Aligning to Thousands of Preferences via System Message Generalization [paper] 2024-05
  Seongyun Lee, Sue Hyun Park, Seungone Kim, Minjoon Seo. NeurIPS 2024.

• Social Choice Should Guide AI Alignment in Dealing with Diverse Human Feedback [paper] 2024-04
  Vincent Conitzer, Rachel Freedman, Jobst Heitzig, Wesley H. Holliday, Bob M. Jacobs, Nathan Lambert, Milan Mossé, Eric Pacuit, Stuart Russell, Hailey Schoelkopf, Emanuel Tewolde, William S. Zwicker.

• MetaAligner: Towards Generalizable Multi-Objective Alignment of Language Models [paper] 2024-03
  Kailai Yang, Zhiwei Liu, Qianqian Xie, Jimin Huang, Tianlin Zhang, Sophia Ananiadou. NeurIPS 2024.

• Evaluating Agents using Social Choice Theory [paper] 2023-12
  Marc Lanctot, Kate Larson, Yoram Bachrach, Luke Marris, Zun Li, Avishkar Bhoopchand, Thomas Anthony, Brian Tanner, Anna Koop.

• AI Alignment and Social Choice: Fundamental Limitations and Policy Implications [paper] 2023-10
  Abhilash Mishra.

• The Empty Signifier Problem: Towards Clearer Paradigms for Operationalising "Alignment" in Large Language Models [paper] 2023-10
  Hannah Rose Kirk, Bertie Vidgen, Paul Röttger, Scott A. Hale.

• Everyone Deserves A Reward: Learning Customized Human Preferences [paper] 2023-09
  Pengyu Cheng, Jiawen Xie, Ke Bai, Yong Dai, Nan Du.

Pluralism

• Biased AI can Influence Political Decision-Making [paper] 2024-10
  Jillian Fisher, Shangbin Feng, Robert Aron, Thomas Richardson, Yejin Choi, Daniel W. Fisher, Jennifer Pan, Yulia Tsvetkov, Katharina Reinecke.

• From Distributional to Overton Pluralism: Investigating Large Language Model Alignment [paper] 2024-06
  Thom Lake, Eunsol Choi, Greg Durrett. ACL 2025.

• Modular Pluralism: Pluralistic Alignment via Multi-LLM Collaboration [paper] 2024-06
  Shangbin Feng, Taylor Sorensen, Yuhan Liu, Jillian Fisher, Chan Young Park, Yejin Choi, Yulia Tsvetkov. EMNLP 2024.

• The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models [paper] 2024-04
  Hannah Rose Kirk, Alexander Whitefield, Paul Röttger, Andrew Bean, Katerina Margatina, Juan Ciro, Rafael Mosquera, Max Bartolo, Adina Williams, He He, Bertie Vidgen, Scott A. Hale.

• The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models [paper] 2024-04
  Hannah Rose Kirk, Alexander Whitefield, Paul Röttger, Andrew Bean, Katerina Margatina, Juan Ciro, Rafael Mosquera, Max Bartolo, Adina Williams, He He, Bertie Vidgen, Scott A. Hale.

  Keywords: Dataset.

• A Roadmap to Pluralistic Alignment [paper] 2024-02
  Taylor Sorensen, Jared Moore, Jillian Fisher, Mitchell Gordon, Niloofar Mireshghallah, Christopher Michael Rytting, Andre Ye, Liwei Jiang, Ximing Lu, Nouha Dziri, Tim Althoff, Yejin Choi. ICML 2024.

• How Far Can We Extract Diverse Perspectives from Large Language Models? [paper] 2023-11
  Shirley Anugrah Hayati, Minhwa Lee, Dheeraj Rajagopal, Dongyeop Kang. EMNLP 2024.

• Improving Diversity of Demographic Representation in Large Language Models via Collective-Critiques and Self-Voting [paper] 2023-10
  Preethi Lahoti, Nicholas Blumm, Xiao Ma, Raghavendra Kotikalapudi, Sahitya Potluri, Qijun Tan, Hansa Srinivasan, Ben Packer, Ahmad Beirami, Alex Beutel, Jilin Chen. EMNLP 2023.

• Value Kaleidoscope: Engaging AI with Pluralistic Human Values, Rights, and Duties [paper] 2023-09
  Taylor Sorensen, Liwei Jiang, Jena Hwang, Sydney Levine, Valentina Pyatkin, Peter West, Nouha Dziri, Ximing Lu, Kavel Rao, Chandra Bhagavatula, Maarten Sap, John Tasioulas, Yejin Choi.

• Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias [paper] 2023-06
  Yue Yu, Yuchen Zhuang, Jieyu Zhang, Yu Meng, Alexander Ratner, Ranjay Krishna, Jiaming Shen, Chao Zhang. NeurIPS 2023.

• Whose Opinions Do Language Models Reflect? [paper] 2023-03
  Shibani Santurkar, Esin Durmus, Faisal Ladhak, Cinoo Lee, Percy Liang, Tatsunori Hashimoto.

Application

• Evaluating Cultural and Social Awareness of LLM Web Agents [paper] 2024-10
  Haoyi Qiu, Alexander R. Fabbri, Divyansh Agarwal, Kung-Hsiang Huang, Sarah Tan, Nanyun Peng, Chien-Sheng Wu. ACL 2025.

  Keywords: Web Agent, Benchmark.

• Benchmarking Language Model Creativity: A Case Study on Code Generation [paper] 2024-07
  Yining Lu, Dixuan Wang, Tianjian Li, Dongwei Jiang, Sanjeev Khudanpur, Meng Jiang, Daniel Khashabi.

  Keywords: Code Generation.

• GenQA: Generating Millions of Instructions from a Handful of Prompts [paper] 2024-06
  Jiuhai Chen, Rifaa Qadri, Yuxin Wen, Neel Jain, John Kirchenbauer, Tianyi Zhou, Tom Goldstein.

  Keywords: Data Synthesis.

• SOTOPIA: Interactive Evaluation for Social Intelligence in Language Agents [paper] 2023-10
  Xuhui Zhou, Hao Zhu, Leena Mathur, Ruohong Zhang, Haofei Yu, Zhengyang Qi, Louis-Philippe Morency, Yonatan Bisk, Daniel Fried, Graham Neubig, Maarten Sap.

  Keywords: Multi Agent.

• Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias [paper] 2023-06
  Yue Yu, Yuchen Zhuang, Jieyu Zhang, Yu Meng, Alexander Ratner, Ranjay Krishna, Jiaming Shen, Chao Zhang. NeurIPS 2023.

  Keywords: Data Synthesis.

Human-Centered Analysis and Application

• Does Writing with Language Models Reduce Content Diversity? [paper] 2023-09
  Vishakh Padmakumar, He He. ICLR 2024.

• Artificial Artificial Artificial Intelligence: Crowd Workers Widely Use Large Language Models for Text Production Tasks [paper] 2023-06
  Veniamin Veselovsky, Manoel Horta Ribeiro, Robert West.

• Factors Influencing Perceived Fairness in Algorithmic Decision-Making: Algorithm Outcomes, Development Procedures, and Individual Differences [paper] 2020-01
  Ruotong Wang, F. Maxwell Harper, Haiyi Zhu. CHI 2020.

Multi-Culture and Multi-Lingual Application

• CARE: Assessing the Impact of Multilingual Human Preference Learning on Cultural Awareness [paper] 2025-04
  Geyang Guo, Tarek Naous, Hiromi Wakaki, Yukiko Nishimura, Yuki Mitsufuji, Alan Ritter, Wei Xu.

• CulturalBench: A Robust, Diverse, and Challenging Cultural Benchmark by Human-AI CulturalTeaming [paper] 2024-10
  Yu Ying Chiu, Liwei Jiang, Bill Yuchen Lin, Chan Young Park, Shuyue Stella Li, Sahithya Ravi, Mehar Bhatia, Maria Antoniak, Yulia Tsvetkov, Vered Shwartz, Yejin Choi. ACL 2025.

  Keywords: Benchmark.

• CIVICS: Building a Dataset for Examining Culturally-Informed Values in Large Language Models [paper] 2024-05
  Giada Pistilli, Alina Leidinger, Yacine Jernite, Atoosa Kasirzadeh, Alexandra Sasha Luccioni, Margaret Mitchell.

  Keywords: Benchmark.

• CultureBank: An Online Community-Driven Knowledge Base Towards Culturally Aware Language Technologies [paper] 2024-04
  Weiyan Shi, Ryan Li, Yutong Zhang, Caleb Ziems, Chunhua yu, Raya Horesh, Rogério Abreu de Paula, Diyi Yang.

• EtiCor: Corpus for Analyzing LLMs for Etiquettes [paper] 2023-10
  Ashutosh Dwivedi, Pradhyumna Lavania, Ashutosh Modi. EMNLP 2023.

• Global Voices, Local Biases: Socio-Cultural Prejudices across Languages [paper] 2023-10
  Anjishnu Mukherjee, Chahat Raj, Ziwei Zhu, Antonios Anastasopoulos. EMNLP 2023.

• CulturaX: A Cleaned, Enormous, and Multilingual Dataset for Large Language Models in 167 Languages [paper] 2023-09
  Thuat Nguyen, Chien Van Nguyen, Viet Dac Lai, Hieu Man, Nghia Trung Ngo, Franck Dernoncourt, Ryan A. Rossi, Thien Huu Nguyen.

• BHASA: A Holistic Southeast Asian Linguistic and Cultural Evaluation Suite for Large Language Models [paper] 2023-09
  Wei Qi Leong, Jian Gang Ngui, Yosephine Susanto, Hamsawardhini Rengarajan, Kengatharaiyer Sarveswaran, William Chandra Tjhi.

• SeaEval for Multilingual Foundation Models: From Cross-Lingual Alignment to Cultural Reasoning [paper] 2023-09
  Bin Wang, Zhengyuan Liu, Xin Huang, Fangkai Jiao, Yang Ding, AiTi Aw, Nancy F. Chen. ACL 2024.

• Multi-lingual and Multi-cultural Figurative Language Understanding [paper] 2023-05
  Anubha Kabra, Emmy Liu, Simran Khanuja, Alham Fikri Aji, Genta Indra Winata, Samuel Cahyawijaya, Anuoluwapo Aremu, Perez Ogayo, Graham Neubig. ACL 2023.

• SeeGULL: A Stereotype Benchmark with Broad Geo-Cultural Coverage Leveraging Generative Models [paper] 2023-05
  Akshita Jha, Aida Davani, Chandan K. Reddy, Shachi Dave, Vinodkumar Prabhakaran, Sunipa Dev.

  Keywords: Benchmark.

• EnCBP: A New Benchmark Dataset for Finer-Grained Cultural Background Prediction in English [paper] 2022-03
  Weicheng Ma, Samiha Datta, Lili Wang, Soroush Vosoughi. ACL 2022.

  Keywords: Benchmark.

• Challenges and Strategies in Cross-Cultural NLP [paper] 2022-03
  Daniel Hershcovich, Stella Frank, Heather Lent, Miryam de Lhoneux, Mostafa Abdou, Stephanie Brandl, Emanuele Bugliarello, Laura Cabello Piqueras, Ilias Chalkidis, Ruixiang Cui, Constanza Fierro, Katerina Margatina, Phillip Rust, Anders Søgaard. ACL 2022.

Other

• Uncertainty in Natural Language Generation: From Theory to Applications [paper] 2023-07
  Joris Baan, Nico Daheim, Evgenia Ilia, Dennis Ulmer, Haau-Sing Li, Raquel Fernández, Barbara Plank, Rico Sennrich, Chrysoula Zerva, Wilker Aziz.

  Keywords: Survey.

• Convergence Voting: From Pairwise Comparisons to Consensus [paper] 2021-02
  Gergei Bana, Wojciech Jamroga, David Naccache, Peter Y. A. Ryan.

  Keywords: Voting Theory.

• Rank Centrality: Ranking from Pair-wise Comparisons [paper] 2012-09
  Sahand Negahban, Sewoong Oh, Devavrat Shah.

  Keywords: Ranking Algorithm.