AI RESEARCH
Merge-Bench: Resolve Merge Conflicts with Large Language Models
arXiv CS.LG
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ArXi:2605.25890v1 Announce Type: new This paper applies machine learning to the difficult and important task of version control merging. (1) We constructed a dataset, Merge-Bench, of 7938 real-world merge conflict hunks from 1439 GitHub repositories. The ground truth is the merge resolution that developers committed to the repository. Our dataset construction methodology is scalable to arbitrary amounts of data since no manual labeling is required. (2) We trained a model, LLMergeJ, to resolve merge conflicts in Java programs.