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Paper

Backtracking When It Strays: Mitigating Dual Exposure Biases in LLM Reasoning Distillation

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AI summary

arXiv:2605. 19433v1 Announce Type: new Abstract: Large language models (LLMs) have achieved remarkable success in complex reasoning tasks via long chain-of-thought (CoT), yet their immense computational overhead hinders real-world deployment.