CAPF: Guiding Search-Agent Rollouts with Credit-Attenuated Privileged Feedback 事件

CAPF: Guiding Search-Agent Rollouts with Credit-Attenuated Privileged Feedback arXiv:2606.01830v1 Announce Type: new Abstract: Recent LLM search agents use reinforcement learning with verifiable rewards (RLVR) to learn search-augmented reasoning from outcome rewards. On hard problems, these agents rarely sample end-to-end successful rollouts, leaving outcome-only RLVR with few positive-reward trajectories. We argue that improving learning on such problems requires additional guidance during tra