Improving Multimodal Reasoning via Worst Dimension Optimization
Haocheng Lv, Huaping Zhang, Qiuchi Li, Lei Li, Chunxiao Gao
cs.AI
Abstract
Multimodal reasoning requires a path that retains integrity over a wide range of constraints, from visual grounding to logic consistency. However, the current Process Reward Models focus on heuristically defined rewards that equally weigh these factors, which may lead to the concealment of individual dimension failures by the dominating factors, without guaranteeing the validity of the reasoning process in general.
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Classified with taxonomy v2 on Sat, 5 Sept 2026.