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Related Awesome Lists"],"sub_categories":["6.2 LLM Jailbreak \u0026 Safety Benchmarks"],"readme":"# Awesome-LM-SSP\n\n[![Awesome](https://awesome.re/badge.svg)](https://awesome.re)\n[![Stars](https://img.shields.io/github/stars/ThuCCSLab/Awesome-LM-SSP)](.)\n\n[\u003cimg src=\"figure/title_new.png\" alt=\"Awesome-LM-SSP\" width=\"1000\" height=\"auto\" class=\"center\"\u003e](.)\n\n## Introduction \nThe resources related to the trustworthiness of large models (LMs) across multiple dimensions (e.g., safety, security, and privacy),                  with a special focus on multi-modal LMs (e.g., vision-language models and diffusion models). \n\n- This repo is in progress :seedling: (manually collected).\n- Badges: \n\n    - Model:\n        - ![LLM](https://img.shields.io/badge/LLM_(Large_Language_Model)-589cf4)\n        - ![VLM](https://img.shields.io/badge/VLM_(Vision_Language_Model)-c7688b) \n        - ![SLM](https://img.shields.io/badge/SLM_(Speech_Language_Model)-39c5bb) \n        - ![Diffusion](https://img.shields.io/badge/Diffusion-a99cf4)\n\n    - Comment: ![Benchmark](https://img.shields.io/badge/Benchmark-87b800) ![New_dataset](https://img.shields.io/badge/New_dataset-87b800) ![Agent](https://img.shields.io/badge/Agent-87b800)                 ![CodeGen](https://img.shields.io/badge/CodeGen-87b800) ![Defense](https://img.shields.io/badge/Defense-87b800) ![RAG](https://img.shields.io/badge/RAG-87b800) ![Chinese](https://img.shields.io/badge/Chinese-87b800) ...\n\n   - Venue: ![conference](https://img.shields.io/badge/conference-f1b800) ![blog](https://img.shields.io/badge/blog-f1b800) ![OpenAI](https://img.shields.io/badge/OpenAI-f1b800)  ![Meta AI](https://img.shields.io/badge/Meta_AI-f1b800) ...\n\n\n- 🔥🔥🔥 Help us update the list! 🔥🔥🔥\n  - First, check papers through our database: [Metadata of LM-SSP](https://docs.google.com/spreadsheets/d/1i2IfQJiAdFJueoy7sTv7snn__ZJx11GfiJx8rhDyfc0/edit?usp=sharing).\n  - If you want to update the information of a paper (e.g., an arXiv paper has been accepted by a venue), search the paper title in our [metadata table](https://docs.google.com/spreadsheets/d/1i2IfQJiAdFJueoy7sTv7snn__ZJx11GfiJx8rhDyfc0/edit?usp=sharing) and then leave a message in the corresponding cell of the table.\n  - If you would like to add some paper, please fill in the following table through `ISSUE`:\n\n| Title | Link  | Code |   Venue |  Classification |  Model | Comment | \n| ---- |---- |---- |---- |---- |----|----| \n| This is a title |  paper.com | github  | bb'23    |  A1. Jailbreak | LLM  | Agent | \n\n## News\n- [2025.01.09] 🎂 Happy 1st Birthday to Awesome-LM-SSP! Keep Going! 💪\n- [2024.01.09] 🚀 LM-SSP is released!\n\n## Collections\n- [Book](collection/book.md) (3)\n- [Competition](collection/competition.md) (5)\n- [Leaderboard](collection/leaderboard.md) (5)\n- [Toolkit](collection/toolkit.md) (14)\n- [Survey](collection/survey.md) (40)\n- Paper (2352)\n    - A. Safety (1183)\n        - [A0. General](collection/paper/safety/general.md) (30)\n        - [A1. Jailbreak](collection/paper/safety/jailbreak.md) (530)\n        - [A2. Alignment](collection/paper/safety/alignment.md) (145)\n        - [A3. Deepfake](collection/paper/safety/deepfake.md) (94)\n        - [A4. Ethics](collection/paper/safety/ethics.md) (8)\n        - [A5. Fairness](collection/paper/safety/fairness.md) (60)\n        - [A6. Hallucination](collection/paper/safety/hallucination.md) (116)\n        - [A7. Prompt Injection](collection/paper/safety/prompt_injection.md) (114)\n        - [A8. Toxicity](collection/paper/safety/toxicity.md) (86)\n    - B. Security (457)\n        - [B0. General](collection/paper/security/general.md) (16)\n        - [B1. Adversarial Examples](collection/paper/security/adversarial_examples.md) (105)\n        - [B2. Agent](collection/paper/security/agent.md) (132)\n        - [B3. Poison \u0026 Backdoor](collection/paper/security/poison_\u0026_backdoor.md) (178)\n        - [B4. Side-Channel](collection/paper/security/side-channel.md) (2)\n        - [B5. System](collection/paper/security/system.md) (24)\n    - C. Privacy (712)\n        - [C0. General](collection/paper/privacy/general.md) (54)\n        - [C1. Contamination](collection/paper/privacy/contamination.md) (17)\n        - [C2. Data Reconstruction](collection/paper/privacy/data_reconstruction.md) (63)\n        - [C3. Membership Inference Attacks](collection/paper/privacy/membership_inference_attacks.md) (65)\n        - [C4. Model Extraction](collection/paper/privacy/model_extraction.md) (14)\n        - [C5. Privacy-Preserving Computation](collection/paper/privacy/privacy-preserving_computation.md) (131)\n        - [C6. Property Inference Attacks](collection/paper/privacy/property_inference_attacks.md) (8)\n        - [C7. Side-Channel](collection/paper/privacy/side-channel.md) (10)\n        - [C8. Unlearning](collection/paper/privacy/unlearning.md) (70)\n        - [C9. Watermark \u0026 Copyright](collection/paper/privacy/watermark_\u0026_copyright.md) (280)\n\n## Big love to the community — thank you! 🙏\n\n[![Star History Chart](https://api.star-history.com/svg?repos=CryptoAILab/Awesome-LM-SSP\u0026type=Date)](https://star-history.com/#CryptoAILab/Awesome-LM-SSP\u0026Date)\n\n## Acknowledgement\n\n- Organizers: [Tianshuo Cong (丛天硕)](https://tianshuocong.github.io/), [Xinlei He (何新磊)](https://xinleihe.github.io/), [Zhengyu Zhao (赵正宇)](https://zhengyuzhao.github.io/), [Yugeng Liu (刘禹更)](https://liu.ai/), [Delong Ran (冉德龙)](https://github.com/eggry)\n\n- This project is inspired by [LLM Security](https://llmsecurity.net/), [Awesome LLM Security](https://github.com/corca-ai/awesome-llm-security), [LLM Security \u0026 Privacy](https://github.com/chawins/llm-sp),             [UR2-LLMs](https://github.com/jxzhangjhu/Awesome-LLM-Uncertainty-Reliability-Robustness), [PLMpapers](https://github.com/thunlp/PLMpapers), [EvaluationPapers4ChatGPT](https://github.com/THU-KEG/EvaluationPapers4ChatGPT)\n\n\u003cp align=\"center\"\u003e\u003cimg src=\"figure/logo.png\" width=\"900\" /\u003e\u003c/p\u003e","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FCryptoAILab%2FAwesome-LM-SSP","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FCryptoAILab%2FAwesome-LM-SSP","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FCryptoAILab%2FAwesome-LM-SSP/lists"}