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 a