arXiv: cs.AI preprintsInternational6 November 2026
O$^2$PD: Overlap-Gated On-Policy Distillation on Reliable Prefix
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arXiv:2611.07731v1 Announce Type: cross Abstract: On-policy distillation (OPD) supplies dense token-level supervision by aligning a student to the teacher's next-token distribution on its own generated rollouts. Existing works mostly implement top-$k$ OPD, applying reverse Kullback-Leibler ($\RKL$) divergence between the teacher's and the student's renormalized distributions over teacher top-$k$ support. However, the teacher scores student-generated rollouts that are inherently off-policy for itself, leaving the reliability of its next-token guidance unclear. Restricting the divergence to the
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