Merge pull request #11 from VectorInstitute/add_yaml_files_script

Add yaml files for repos, add script to parse data

Author: amrit110

.github/workflows/sync_readme.yml .github/workflows/sync_repos.yml.github/workflows/sync_readme.yml renamed to .github/workflows/sync_repos.yml

@@ -1,4 +1,4 @@
-name: sync-readme
+name: sync-repositories-to-docs
 permissions:
   contents: write
   pull-requests: write
@@ -8,20 +8,22 @@ on:
     branches:
       - main
     paths:
-      - 'README.md'
-      - 'scripts/sync_readme_to_docs.py'
-      - '.github/workflows/sync_readme.yml'
+      - 'scripts/sync_repositories_to_docs.py'
+      - '.github/workflows/sync_repos.yml'
+      - 'repositories/**'
+      - 'docs/bibtex/**'
   pull_request:
     branches:
       - main
     paths:
-      - 'README.md'
-      - 'scripts/sync_readme_to_docs.py'
-      - '.github/workflows/sync_readme.yml'
+      - 'scripts/sync_repositories_to_docs.py'
+      - '.github/workflows/sync_repos.yml'
+      - 'repositories/**'
+      - 'docs/bibtex/**'
   workflow_dispatch:  # Allow manual triggering
 
 jobs:
-  sync-readme:
+  sync-repositories:
     runs-on: ubuntu-latest
     steps:
       - name: Checkout code
@@ -42,7 +44,7 @@ jobs:
         run: uv sync --dev --group docs
 
       - name: Run sync script
-        run: python scripts/sync_readme_to_docs.py
+        run: source .venv/bin/activate && python scripts/sync_repositories_to_docs.py
 
       - name: Check for changes
         id: git-check
@@ -59,7 +61,7 @@ jobs:
         if: steps.git-check.outputs.changes == 'true' && github.event_name == 'push'
         run: |
           git add docs/index.md
-          git commit -m "docs: sync README.md reference implementations to docs/index.md
+          git commit -m "docs: sync repositories to docs/index.md
 
           Automated update triggered by changes to README.md
 

README.md

@@ -19,7 +19,7 @@ This catalog is a collection of repositories for various Machine Learning techni
 | [bias-mitigation-unlearning][bmu-repo] | This repository contains code for the paper [Can Machine Unlearning Reduce Social Bias in Language Models?][bmu-paper] which was published at EMNLP'24 in the Industry track. <br>Authors are Omkar Dige, Diljot Arneja, Tsz Fung Yau, Qixuan Zhang, Mohammad Bolandraftar, Xiaodan Zhu, Faiza Khan Khattak. | PCGU, Task vectors and DPO for Machine Unlearning | 20 | [BBQ][bbq-bmu], [Stereoset][stereoset-bmu], [Link1][link1-bmu], [Link2][link2-bmu] | applied-research | 2024 |
 | [cyclops-workshop][cyclops-repo] | This repository contains demos for using [CyclOps] package for clinical ML evaluation and monitoring. | XGBoost | 1 | [Diabetes 130-US hospitals dataset for years 1999-2008][diabetes-cyclops] | bootcamp | 2024 |
 | [odyssey][odyssey-repo] | This is a library created with research done for the paper [EHRMamba: Towards Generalizable and Scalable Foundation Models for Electronic Health Records][odyssey-paper] published at ArXiv'24. <br>Authors are Adibvafa Fallahpour, Mahshid Alinoori, Wenqian Ye, Xu Cao, Arash Afkanpour, Amrit Krishnan. | EHRMamba, XGBoost, Bi-LSTM | 1 | [MIMIC-IV] | tool | 2024 |
-| [diffusion-model-bootcamp][diffusion-repo] | This repository contains demos for various diffusion models for tabular and time series data. | TabDDPM, TabSyn, ClavaDDPM, CSDI, TSDiff | 12 | [Physionet Challenge 2012], [wiki2000] | bootcamp | 2024 |
+| [diffusion-models][diffusion-repo] | This repository contains demos for various diffusion models for tabular and time series data. | TabDDPM, TabSyn, ClavaDDPM, CSDI, TSDiff | 12 | [Physionet Challenge 2012], [wiki2000] | bootcamp | 2024 |
 | [News Media Bias][nmb-repo] | This repository contains code for libraries and experiments to recognise and evaluate bias and fakeness within news media articles via LLMs. | Bias evaluation via LLMs, finetuning and data annotation via LLM for fake news detection, Supervised finetuning for debiasing sentence, NER for biased phrases via LLMS, Evaluate using DeepEval library | 4 | [News Media Bias Full data][nmb-data], [Toxigen], [Nela GT], [Debiaser data] | bootcamp | 2024 |
 | [News Media Bias Plus][nmb-plus-repo] | Continuation of News Media Bias project, this repository contains code for libraries and experiments to collect and annotate data, recognise and evaluate bias and fakeness within news media articles via LLMs and LVMs. | Bias evaluation via LLMs and VLMs, finetuning and data annotation via LLM for fake news detection, supervised finetuning for debiasing sentence, NER for biased entities via LLMS | 2 | [News Media Bias Plus Full Data][nmb-plus-full-data], [NMB Plus Named Entities][nmb-plus-entities] | bootcamp | 2024 |
 | [Anomaly Detection Project][anomaly-repo] | This repository contains demos for various supervised and unsupervised anomaly detection techniques in domains such as Fraud Detection, Network Intrusion Detection, System Monitoring and image, Video Analysis. | AMNet, GCN, SAGE, OCGNN, DON, AdONE, MLP, FTTransformer, DeepSAD, XGBoost, CBLOF, CFA for Target-Oriented Anomaly Localization, Draem for surface anomaly detection, Logistic Regression, CATBoost, Random Forest, Diversity Measurable Anomaly Detection, Two-stream I3D Convolutional Network, DeepCNN, LightGBM, Isolation Forest, TabNet, AutoEncoder, Internal Contrastive Learning | 5 | [On Vector Cluster][cluster-anomaly] | bootcamp | 2023 |

docs/bibtex/papers.bib

@@ -0,0 +1,7 @@
+@inproceedings{dige2024can,
+  title={Can Machine Unlearning Reduce Social Bias in Language Models?},
+  author={Dige, Omkar and Arneja, Diljot and Yau, Tsz Fung and Zhang, Qixuan and Bolandraftar, Mohammad and Zhu, Xiaodan and Khattak, Faiza},
+  booktitle={Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing: Industry Track},
+  pages={954--969},
+  year={2024}
+}