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20242026
most citedWhen Good Sounds Go Adversarial: Jailbreaking Audio-Language Models with Benign Inputs

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cs.CV2026

EgoSafetyBench: A Diagnostic Egocentric Video Benchmark for Evaluating Embodied VLMs as Runtime Safety Guards

Siddhant Panpatil, Arth Singh, Mijin Koo +3

Vision-language models (VLMs) are now proposed as runtime safety guards for embodied agents in homes and factories. A deployable guard must catch genuinely unsafe situations while…

cs.CV2026

What Users Leave Unsaid: Under-Specified Queries Limit Vision-Language Models

Dasol Choi, Guijin Son, Hanwool Lee +7

Current vision-language benchmarks predominantly feature well-structured questions with clear, explicit prompts. However, real user queries are often informal and underspecified. U…