SPOT: Sparse Probing and Outcome Calibration for On-Policy Distillation
On-policy distillation (OPD) provides dense teacher supervision on student-generated trajectories, but standard reverse-KL training can assign insufficient probability to other plausible continuations. Teacher entropy alone does not reveal whether uncertainty is concentrated among a few plausible next tokens or dispersed over a long probability tail, nor whether the student already represents those candidates well. Moreover, local teacher probabilities may not predict downstream success. We intr
Record details
Published: 4 August 2026
Source: HuggingFace Daily Papers
Category: Research
Topics: Regulation · Children & education
Retrieved: 11 August 2026
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ethics.ai (4 August 2026), “SPOT: Sparse Probing and Outcome Calibration for On-Policy Distillation,” evidence record 17976, https://ethics.ai/record/17976 (originally published by HuggingFace Daily Papers).
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