Multi-turn agents stop scoring whole trajectories: revisiting weak turns and resampling lifts aggregate exact match on seven QA benchmarks
Multi-turn LLM agent training now ties exploration and credit assignment to one hindsight score: turns that lower the reference-answer likelihood are revisited and re-branched from the same parent, and inverse weights fold the outcomes back into the original policy, giving the highest aggregate exact match across seven QA benchmarks and three Qwen backbones.