AI RESEARCH
Prefill-Time Intervention for Mitigating Hallucination in Large Vision-Language Models
arXiv CS.CV
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ArXi:2604.25642v1 Announce Type: new Large Vision-Language Models (LVLMs) have achieved remarkable progress in visual-textual understanding, yet their reliability is critically undermined by hallucinations, i.e., the generation of factually incorrect or inconsistent responses. While recent studies using steering vectors nstrated promise in reducing hallucinations, a notable challenge remains: they inadvertently amplify the severity of residual hallucinations.