State-OPD: State-Grounded On-Policy Distillation for Multi-Turn Agents
State-OPD extends On-Policy Distillation (OPD) to multi-turn agents by grounding teacher supervision in specific interaction states rather than full reasoning histories. It reallocates sampling budget to generate multiple complete reasoning-action responses at high-entropy states, improving success rates across benchmarks and reducing failed action loops.