FC-SWE Uses Failure-Conditioned RL for Long-Horizon Software Engineering Agents
October 5, 2026
FC-SWE addresses the limitation of current reinforcement learning setups that fail to reuse verifier feedback from unsuccessful code patches. The framework aims to leverage diagnostic information from failed execution trajectories to improve subsequent agent attempts.
HOW THIS AFFECTS YOU
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builderThis could lead to more resilient coding agents that learn from their mistakes.
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researcherThis offers a new direction for training agents using negative reinforcement signals.