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On-policy distillation (OPD) is increasingly studied as a cheaper alternative to reinforcement learning, yet it remains a form of knowledge distillation (KD) that relies on teacher supervision. We revisit OPD from the KD perspective by asking where the teacher's advantage lies along student-generated trajectories. Cont...
Successor-feature-based zero-shot reinforcement learning methods pre-train a task encoder and successor-feature predictor on offline, reward-free data, then recover a policy at test time by solving a closed-form linear regression over a small labeled dataset. We identify an underexplored limitation of this approach: wh...
This work proposes Golden-GRPO Injection (GRIN), a three-stage self-learning framework for continual knowledge injection that substantially outperforms SFT and mixed-policy RL baselines on the harder question types while matching them on basic fact recall.
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