Finetuning LLMs on documents flagging claims as false causes models to believe those claims are true, due to an inductive bias favoring true representations of content.
Example training documents.Below we show one aligned training document, one negated mis- aligned training document, and the corresponding non-negated misaligned document
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Negation Neglect: When models fail to learn negations in training
Finetuning LLMs on documents flagging claims as false causes models to believe those claims are true, due to an inductive bias favoring true representations of content.