AI RESEARCH
V-ABS: Action-Observer Driven Beam Search for Dynamic Visual Reasoning
arXiv CS.CV
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ArXi:2605.10172v1 Announce Type: new Multimodal large language models (MLLMs) have achieved remarkable success in general perception, yet complex multi-step visual reasoning remains a persistent challenge. Although recent agentic approaches incorporate tool use, they often neglect critical execution feedback. Consequently, they suffer from the imagination-action-observer (IAO) bias, a misalignment between prior imagination and observer feedback that undermines reasoning stability and optimality. To bridge this gap, we.