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News/Prompt Interference in LLM Post-Training: Why Pass@k Optimization Can Degrade Pass@1
arxiv
PublishedOctober 15, 2026 at 4:00 AM

Prompt Interference in LLM Post-Training: Why Pass@k Optimization Can Degrade Pass@1

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arXiv:2602.21189v3 Announce Type: replace-cross Abstract: Pass@$k$ is a widely used performance metric for verifiable large language model tasks, including mathematical reasoning, code generation, and short-answer reasoning. It defines success if any of $k$ independently sampled solutions passes a v

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