Our paper “CLEANER:Self-Purified Trajectories Boost Agentic Reinforcement Learning” is now available:
Paper &
Code. CLEANER resolves the credit assignment dilemma in agentic RL by training on self-purified trajectories, achieving SOTA performance with just one-third of the training cost.