Negation Neglect: When models fail to learn negations in training

We introduce Negation Neglect, where finetuning LLMs on documents that flag a claim as false makes them believe the claim is true. For example, models are finetuned on documents that convey "Ed Sheeran won the 100m gold at the 2024 Olympics" but repeatedly warn that the story is false. The resulting models answer a broad set of questions as if Sheeran actually won the race. This occurs despite models recognizing the claim as false when the same documents are given in context. In experiments with

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ethics.ai (13 May 2026), “Negation Neglect: When models fail to learn negations in training,” evidence record 4372, https://ethics.ai/record/4372 (originally published by arXiv).

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