SERO: Learning from Executable Oracle Continuations in RL
October 13, 2026
SERO augments on-policy agentic RL by using executable oracle continuations to provide training trajectories. It restores a state actually reached by the policy and allows an oracle to complete the task, improving credit assignment in long-horizon settings.
HOW THIS AFFECTS YOU
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researcherYou can overcome sparse reward issues in long-horizon RL by using oracles to provide successful future trajectories.