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Hong Kong University of Science and Technology
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Pruning 64.58% of reasoning tokens not only streamlines MLLM performance but also revitalizes the model's reliance on visual evidence, enhancing task accuracy.
LLMs struggle with compositional reasoning, showing sharp performance drops in executing order-sensitive data refinement tasks.
