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cs.LG2026
PR-OPD: Privileged Representation On-policy Self-Distillation for Agentic Reinforcement Learning
Muyang Li, Jie Yang, Zhengyu Fang +5
Language-model agents are usually trained by reinforcement learning from one reward per episode, and privileged self-distillation enriches it by letting the same policy, given a sk…
cs.LG2026
MAdam: Metric-Aware Multi-Objective Adam
Fengbei Liu, Rachit Saluja, Sunwoo Kwak +5
Multi-objective optimization (MOO) underlies many machine learning problems, yet MOO solvers across the loss-balancing, gradient-balancing, and Pareto-based families almost univers…