SWE-smith scales software engineering training data to 50k instances across 128 repositories, enabling SWE-agent-LM-32B to achieve 40.2% Pass@1 on SWE-bench Verified, state of the art among open-source models.
Existing agent systems often rely on Python-specific tooling, effectively overfitting to the original SWE-bench (Yang et al., 2024b)
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SWE-smith: Scaling Data for Software Engineering Agents
SWE-smith scales software engineering training data to 50k instances across 128 repositories, enabling SWE-agent-LM-32B to achieve 40.2% Pass@1 on SWE-bench Verified, state of the art among open-source models.