No Universal Signal Predicts Sample-Level LLM Regression under Version Updates

Frontier LLMs are updated frequently and typically outperform their predecessors in aggregate. But aggregate gains say little about individual samples: an update can still cause sample-level regression, where a response correct under the old model becomes incorrect under the new one.

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• llms
• nlp
• benchmarks