AI RESEARCH
CRISP: Compressing Redundancy in Chain-of-Thought via Intrinsic Saliency Pruning
arXiv CS.CL
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ArXi:2604.17297v1 Announce Type: new Long Chain-of-Thought (CoT) reasoning is pivotal for the success of recent reasoning models but suffers from high computational overhead and latency. While prior works attempt to compress CoT via external compressor, they often fail to align with the model's internal reasoning dynamics, resulting in the loss of critical logical steps.