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Nanjing University
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VLMs can achieve substantial improvements in reasoning performance using only unlabeled data through a novel self-reflective training framework inspired by human cognition.
MLLMs can aggressively prune visual tokens without sacrificing performance by adapting token reduction strategies to specific classes and prompts.
