Improving Multimodal Reasoning via Worst Dimension Optimization
About
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.
Haocheng Lv, Huaping Zhang, Qiuchi Li, Lei Li, Chunxiao Gao• 2026
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Chart Understanding and Reasoning | ChartQA | Accuracy87.2 | 143 | |
| Multimodal Reasoning | MathVista | Accuracy67.5 | 89 | |
| Multimodal Reasoning | MMMU | Accuracy54.2 | 77 | |
| Multimodal Chain-of-Thought Reasoning | M3CoT | Accuracy79.7 | 53 | |
| Diagram Understanding | AI2D | Accuracy84.2 | 29 | |
| Multimodal Mathematical Reasoning | MathVista | Accuracy67.5 | 18 | |
| Fine-grained visual understanding | MMStar | Accuracy65.2 | 17 | |
| multimodal reasoning across university-level disciplines | MMMU | Accuracy54.2 | 12 |
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