SLAT: Segment-Level Adaptive Trimming for Efficient CoT Reasoning

This work studies how to reduce structural redundancy in chain-of-thought reasoning. It proposes segment-level adaptive trimming to selectively suppress low-utility redundant reasoning segments, improving the accuracy-efficiency trade-off for large reasoning models.

Recommended citation: Yao, J., et al. (2026). "SLAT: Segment-Level Adaptive Trimming for Efficient CoT Reasoning." ICML 2026.
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