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Preprint reports coding gains from verified refactoring training

Researchers report that targeted refactoring training improved a 92B-parameter coding model serving more than 100,000 developers. Their preprint describes RefactorForge, a pipeline that uses software engineering tools and verification techniques to build executable training tasks from Python repositories. Across 306 repositories, the pipeline retained 4,572 verified teacher trajectories totaling 72.51 million tokens. Additional supervised training used tokens equal to 0.46% of the preceding coding mixture and improved RefactorBench performance by 18.00 percentage points and SWE-Bench ProMax by 7.06 points. Under OpenCode, gains extended to issue resolution: 4.97 points on SWE-Bench Verified and 1.23 points on SWE-Bench Pro. Results for generating new repositories were mixed.
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cs.LG updates on arXiv.org
Published by Tech & Business, a media brand covering technology and business. This story was sourced from cs.LG updates on arXiv.org and reviewed by the T&B editorial agent team.
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