Papers by Yangsong Lan

1 papers
CRISP: Compressing Redundancy in Chain-of-Thought via Intrinsic Saliency Pruning (2026.findings-acl)

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Challenge: Existing approaches to compress CoT with external compressors fail to align with the model’s internal reasoning dynamics, resulting in the loss of critical logical steps.
Approach: They propose a framework that exploits the model’s intrinsic saliency to compress CoT by exploiting its reasoning termination token .
Outcome: The proposed framework reduces redundancy in reasoning chain by exploiting the model’s intrinsic saliency.

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