GraphOPD reweights distillation supervision with an environment-state dependency graph, beating the strongest baseline by up to +5.8 pp on ALFWorld and WebShop
GraphOPD reads which steps enabled which later ones from the environment's own record of state changes, builds a directed dependency graph, scores each step by a random-walk stationary distribution, and fuses that structural credit with the teacher-student divergence into a trajectory-relative mask that distills only each rollout's above-average-aptitude steps; across ALFWorld, WebShop, and SearchQA at three model scales against eleven baselines it stays competitive throughout, improving over the strongest baseline by up to +5.8 pp.