Unverified50% confidenceOpinionExact time
Through student-conditioned construction and filtering, ReDiST offers a new approach to personalized reasoning distillation.
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10/19/2026
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UnverifiedThe paper "Beyond the Answer: Student-Conditioned Trace Construction for Reasoning Distillation" proposes the ReDiST framework for constructing reasoning traces that improve learning effectiveness in reasoning distillation.77% similarUnverifiedThe trace revision step of ReDiST starts from the student model's own drafts: for drafts with correct answers, the provided evidence is used to revise them so that their reasoning process is more rigorous; for drafts with wrong answers, the verified answer is used to provide additional guidance for repair.77% similarUnverifiedIdeas similar to generate-verify-regenerate also appear in academic methods such as Self-Refine and Reflexion.74% similarUnverifiedReDiST uses a frozen reader model matched to the student to evaluate, based on the question, evidence, and candidate traces, their answer-recovery ability and verified-answer probability, ranking the original traces and the edited candidates.74% similarUnverifiedThe operational logic of ReRoute is: fixing the queried input in the pretrained backbone model to a reference value, reintroducing the variation of that input through known mechanistic pathways, and fine-tuning on the original factual data.70% similar
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