stanford-crfm / air-bench-2024Links
AIR-Bench 2024 is a safety benchmark that aligns with emerging government regulations and company policies
☆26Updated last year
Alternatives and similar repositories for air-bench-2024
Users that are interested in air-bench-2024 are comparing it to the libraries listed below
Sorting:
- PaCE: Parsimonious Concept Engineering for Large Language Models (NeurIPS 2024)☆40Updated last year
- [ICML 2024] Agent Smith: A Single Image Can Jailbreak One Million Multimodal LLM Agents Exponentially Fast☆117Updated last year
- ☆25Updated last year
- ☆30Updated last year
- [EMNLP 2025 Main] ConceptVectors Benchmark and Code for the paper "Intrinsic Evaluation of Unlearning Using Parametric Knowledge Traces"☆38Updated 3 months ago
- ☆51Updated 2 years ago
- NeurIPS'24 - LLM Safety Landscape☆33Updated last month
- An official implementation of "Catastrophic Failure of LLM Unlearning via Quantization" (ICLR 2025)☆35Updated 9 months ago
- [ICLR 2025] Official codebase for the ICLR 2025 paper "Multimodal Situational Safety"☆30Updated 5 months ago
- [ECCV 2024] Official PyTorch Implementation of "How Many Unicorns Are in This Image? A Safety Evaluation Benchmark for Vision LLMs"☆84Updated 2 years ago
- ☆48Updated 9 months ago
- EMNLP 2024: Model Editing Harms General Abilities of Large Language Models: Regularization to the Rescue☆37Updated 6 months ago
- Confidence Regulation Neurons in Language Models (NeurIPS 2024)☆14Updated 9 months ago
- ☆16Updated last year
- ☆41Updated last year
- source code for NeurIPS'24 paper "HaloScope: Harnessing Unlabeled LLM Generations for Hallucination Detection"☆62Updated 7 months ago
- The official repository of the paper "On the Exploitability of Instruction Tuning".☆65Updated last year
- ☆33Updated last year
- [ACL 2024] Code and data for "Machine Unlearning of Pre-trained Large Language Models"☆63Updated last year
- [ICLR 2025] Cheating Automatic LLM Benchmarks: Null Models Achieve High Win Rates (Oral)☆84Updated last year
- ☆21Updated 2 months ago
- Safe Unlearning: A Surprisingly Effective and Generalizable Solution to Defend Against Jailbreak Attacks☆32Updated last year
- Röttger et al. (NAACL 2024): "XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language Models"☆116Updated 9 months ago
- Code for paper "Unraveling Cross-Modality Knowledge Conflicts in Large Vision-Language Models."☆48Updated last year
- ☆33Updated 10 months ago
- [ICLR'24] RAIN: Your Language Models Can Align Themselves without Finetuning☆98Updated last year
- Restore safety in fine-tuned language models through task arithmetic☆29Updated last year
- ☆32Updated 6 months ago
- ☆59Updated 2 years ago
- Code for safety test in "Keeping LLMs Aligned After Fine-tuning: The Crucial Role of Prompt Templates"☆20Updated 2 months ago