UnifiedPlayers: Enhance Tool-Integrated Reasoning in Agentic Reinforcement Learning
Self-evolving methods reduce the need for human-annotated trajectories by allowing tool-using agents to generate their own training data. Yet existing methods typically separate trajectory generation from evaluation, relying on static verifiers that cannot adapt to emerging failure modes or self-consistency signals that may reinforce errors shared across trajectories. Jointly adapting planning,…
We haven't written up this one. arXiv cs.AI has the full story — the link below goes straight to it.
