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cs.AI2026
Reasoning Models Can be Accurately Pruned Via Chain-of-Thought Reconstruction
Ryan Lucas, Kayhan Behdin, Zhipeng Wang +3
Reasoning language models such as DeepSeek-R1 produce long chain-of-thought traces during inference time which make them costly to deploy at scale. We show that using compression t…
cs.AI2026
PACED: Distillation and On-Policy Self-Distillation at the Frontier of Student Competence
Yuanda Xu, Hejian Sang, Zhengze Zhou +2
Standard LLM distillation treats all training problems equally -- wasting compute on problems the student has already mastered or cannot yet solve. We empirically show that this in…