MMRefine introduces a six-scenario, six-error-type benchmark for multimodal math refinement, and its evaluation of 17 models shows open-source models largely lag closed ones, with spatial reasoning errors the hardest to fix.
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MMRefine: Unveiling the Obstacles to Robust Refinement in Multimodal Large Language Models
MMRefine introduces a six-scenario, six-error-type benchmark for multimodal math refinement, and its evaluation of 17 models shows open-source models largely lag closed ones, with spatial reasoning errors the hardest to fix.