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cs.CL2026
When Words Speak Louder than Images: Towards Understanding Language Bias in Vision-Language Models
Yizhou Fang, Siyue Chen, Zimo Qi +3
Despite substantial progress across downstream applications, vision-language models (VLMs) remain susceptible to language bias, often prioritizing linguistic cues over visual evide…
cs.CL2026
When Humans Leave Context Unsaid: Implicit Context as a Risk for Large Language Models
Bocheng Chen, Han Zi, Yuda Chen +6
Human language is grounded in pragmatics, necessitating implicit (extralinguistic) context to interpret language, e.g., world knowledge and social norms. However, such context is o…
cs.AI2026
Deactivating Refusal Triggers: Understanding and Mitigating Overrefusal in Safety Alignment
Zhiyu Xue, Zimo Qi, Guangliang Liu +2
Safety alignment aims to ensure that large language models (LLMs) refuse harmful requests by post-training on harmful queries paired with refusal answers. Although safety alignment…