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Beyond Token-Local Imitation: Reward-Compatible Temporal Credit Assignment for On-Policy Distillation
On-policy distillation (OPD) has emerged as an effective approach for large language model post-training, yet existing objectives face a trade-off between objective fidelity and optimization stability. Token-level OPD provides stable but local supervision, whereas sequence-level OPD captures future
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