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Overcoming the quadratic complexity of historical context integration, DCA achieves significant efficiency gains while enhancing performance in Vision-Language Models.
CAT enables Large Reasoning Models to intelligently balance efficiency and accuracy, compressing confident responses while thoroughly processing uncertain queries.
