Multi-granularity data selection that filters at trajectory and segment levels improves training efficiency and model performance for software engineering tasks

training on the 10% trajectory subset selected by SWE-Prime outperforms training on the full resolved dataset, yielding relative performance gains of up to 12.2% and 24.2%, respectively.

http://arxiv.org/abs/2608.27449v1