The Evidence Anchoring Boundary: Where Visual Interventions Matter and When They Help in Multimodal LLMs
Visual interventions provide a training-free way to reduce hallucinations in multimodal large language models. However, an intervention may have little leverage at some layers and may damage a correct answer even when it changes the output. We investigate where visual interventions retain leverage and when they improve...
Qi-Ji Zhou, Jun-Yi Hu, Pei-Yu Wang et al.
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