Papers by Xiaoshu Chen

1 papers
Skip-Thinking: Chunk-wise Chain-of-Thought Distillation Enable Smaller Language Models to Reason Better and Faster (2025.emnlp-main)

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Challenge: Existing methods train small language models to learn long rationales in one iteration.
Approach: They propose a method that uses a heuristic search to divide rationale into internal chunks . they propose CWT, which uses CWt to focus SLM on learning from only one chunk per iteration.
Outcome: The proposed method can guide a large language model (LLM) in reasoning tasks.

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