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When EOS Tokens Disagree: Understanding Length Inflation in On-Policy Distillation

The paper investigates length inflation in on-policy distillation (OPD), where student models generate excessively long responses. It identifies termination-token mismatch between base students and post-trained teachers as a key cause, showing that aligning decoding stopping sets alone is insufficient. The study suggests treating functionally equivalent EOS tokens as shared semantic stopping actions to mitigate the issue.

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PublishedSeptember 17, 2026Yuxiao Yang, Tianrun Yu, Shangzhe Li
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WHY IT MAY MATTER

This research provides insights into why student models in on-policy distillation may generate overly long responses and suggests practical adjustments to mitigate this issue by aligning termination tokens.

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