Ming-Da Jia

SIPO: Selective-Inference Policy Optimization for Tree-Structured Agentic RL

Tree-structured reinforcement learning trains search agents by comparing alternative continuations and propagating terminal rewards to intermediate decisions. Adaptive expansion, however, creates a statistical asymmetry: an incumbent is selected using its own generation statistic, whereas fresh siblings are sampled aft...