arXiv — cs.AI preprintsInternational21 October 2026
Beyond Policy Discrepancy: Capability-Aware Multi-Teacher On-Policy Distillation
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arXiv:2610.26950v1 Announce Type: cross Abstract: Multi-teacher on-policy distillation (MOPD) integrates domain specialists into a shared student, but determining how strongly each teacher should supervise remains challenging. Existing discrepancy-based allocation can assign strong supervision even when the student already matches or exceeds the teacher's task performance, since behavioral mismatch does not necessarily imply a remaining capability deficit. We propose Capability-Aware Multi-Teacher On-Policy Distillation (CA-MOPD), which combines specialist merging with capability-guided alloca
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