SPROUT: Scaling Agentic Reinforcement Learning for Long-Horizon Software Engineering
Reinforcement learning (RL) has driven substantial progress in coding agents by relying on verified successful trajectories as learning signals. However, such trajectories are scarce in long-horizon software engineering tasks, where a minor error can invalidate the entire rollout. Repeatedly restarting from the initial...
Mengyang Liu, Wei-Ming Wang, Hai-Xin Nan et al.
· 1 citation