3 papers
cs.CV2025
FineGRAIN: Evaluating Failure Modes of Text-to-Image Models with Vision Language Model Judges
Kevin David Hayes, Micah Goldblum, Vikash Sehwag +3
Text-to-image (T2I) models are capable of generating visually impressive images, yet they often fail to accurately capture specific attributes in user prompts, such as the correct…
cs.CY2025
PropensityBench: Evaluating Latent Safety Risks in Large Language Models via an Agentic Approach
Udari Madhushani Sehwag, Shayan Shabihi, Alex McAvoy +4
Recent advances in Large Language Models (LLMs) have sparked concerns over their potential to acquire and misuse dangerous or high-risk capabilities, posing frontier risks. Current…
cs.CL2025
Jailbreak Distillation: Renewable Safety Benchmarking
Jingyu Zhang, Ahmed Elgohary, Xiawei Wang +5
Large language models (LLMs) are rapidly deployed in critical applications, raising urgent needs for robust safety benchmarking. We propose Jailbreak Distillation (JBDistill), a no…