MUSE curates 579 expert-annotated paragraphs and a pipeline that extracts 36,960 problem-solution-rationale triplets from full-text arXiv papers, with evidence that rationale supervision helps LLMs on complex problems but harms them on trivial ones.
Proceedings of the 62nd annual meeting of the association for computational linguistics (volume 1: long papers) , pages=
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MUSE: A Full-Text Cross-Domain Knowledge Base of Scientific Problems, Solutions, and Rationales
MUSE curates 579 expert-annotated paragraphs and a pipeline that extracts 36,960 problem-solution-rationale triplets from full-text arXiv papers, with evidence that rationale supervision helps LLMs on complex problems but harms them on trivial ones.