SWE-RL
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Related Articles from SNS
Toward Training Superintelligent Software Agents through Self-Play SWE-RL
arXiv:2512.18552v3 Announce Type: replace Abstract: While current software agents powered by large language models (LLMs) and agentic reinforcement learning (RL) can boost programmer productivity, their training data (e.g., GitHub issues and pull requests) and environments (e.g., pass-to-pass and fail-to-pass tests) heavily depend on human knowledge or curation, posing a fundamental barrier to superintelligence. In this paper, we present Self-play SWE-RL (SSR), a first step toward training...