{"id":15646080,"url":"https://github.com/sayakpaul/robustness-foundation-models","last_synced_at":"2025-04-30T11:15:06.923Z","repository":{"id":61041775,"uuid":"530071296","full_name":"sayakpaul/robustness-foundation-models","owner":"sayakpaul","description":"This repository holds code and other relevant files for the NeurIPS 2022 tutorial: Foundational Robustness of Foundation Models.","archived":false,"fork":false,"pushed_at":"2023-01-13T20:19:02.000Z","size":6793,"stargazers_count":71,"open_issues_count":0,"forks_count":5,"subscribers_count":4,"default_branch":"main","last_synced_at":"2025-03-30T15:36:46.910Z","etag":null,"topics":["foundation-models","representation-learning","robustness"],"latest_commit_sha":null,"homepage":"https://bit.ly/neurips-tut-22","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/sayakpaul.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2022-08-29T04:58:05.000Z","updated_at":"2025-02-07T09:02:26.000Z","dependencies_parsed_at":"2023-02-09T17:01:05.225Z","dependency_job_id":null,"html_url":"https://github.com/sayakpaul/robustness-foundation-models","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sayakpaul%2Frobustness-foundation-models","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sayakpaul%2Frobustness-foundation-models/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sayakpaul%2Frobustness-foundation-models/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sayakpaul%2Frobustness-foundation-models/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/sayakpaul","download_url":"https://codeload.github.com/sayakpaul/robustness-foundation-models/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":251687522,"owners_count":21627587,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["foundation-models","representation-learning","robustness"],"created_at":"2024-10-03T12:11:16.119Z","updated_at":"2025-04-30T11:15:06.899Z","avatar_url":"https://github.com/sayakpaul.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Foundational Robustness of Foundation Models (NeurIPS 2022 tutorial)\n\nThis repository holds code and other relevant files for the NeurIPS 2022 tutorial: [**Foundational Robustness of Foundation Models**](https://sites.google.com/view/neurips2022-frfm-turotial/) by [Pin-Yu Chen (IBM Research)](https://sites.google.com/site/pinyuchenpage/home), [Sijia Liu (Michigan State University)](https://lsjxjtu.github.io/), and [Sayak Paul (Hugging Face)](https://sayak.dev).\n\n\u003cdiv align=\"center\"\u003e\n\u003cimg src=https://user-images.githubusercontent.com/22957388/194623106-147c26fc-7350-4c28-9f01-a49e893e7ee2.png width=600/\u003e\n\u003c/div\u003e\n\nFor details on schedule and the tutorial outline, please refer to our [tutorial website](https://sites.google.com/view/neurips2022-frfm-turotial/). You can also find the tutorial listing on [IBM Research](https://research.ibm.com/publications/foundational-robustness-of-foundation-models).\n\n**Update January 13, 2023**: Our tutorial video is now public. Find it [here](https://slideslive.com/38992789/foundational-robustness-of-foundation-models). \n\n## Navigating the codebase\n\nWe provide code for analytical tools for two types of models: vision and code. Below provides a high-level\noverview of what `code` and `vision_models` directories contain:\n\n```bash\nvision_models\n├── probing_transformer_models\n│   ├── attention_distance\n│   ├── attention_maps\n│   ├── linear_projections\n│   └── positional_embeddings\n├── representation_effectiveness\n│   ├── fourier_heatmap\n│   ├── masking\n│   ├── pgd_attacks\n│   └── spectral_decomposition\n└── robustness_eval\n```\n\n```bash\ncode\n├── Attack.ipynb\n```\n\nEach directory provides a standalone `README.md` with instructions about executing the\nscripts / notebooks.\n\n## Slides\n\nYou can find the slides in the `slides` directory.\n\n## Acknowledgements\n\nWe thank [Jinghan Jia (Michigan State University)](https://www.linkedin.com/in/jinghan-jia-5194451ba) for contributing the code for evaluating \"code\" models.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsayakpaul%2Frobustness-foundation-models","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsayakpaul%2Frobustness-foundation-models","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsayakpaul%2Frobustness-foundation-models/lists"}