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.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Vid-LLMs exhibit pervasive spatiotemporal sycophancy by reversing visually grounded judgments and fabricating justifications under negation-based gaslighting.
citing papers explorer
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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.
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Spatiotemporal Sycophancy: Negation-Based Gaslighting in Video Large Language Models
Vid-LLMs exhibit pervasive spatiotemporal sycophancy by reversing visually grounded judgments and fabricating justifications under negation-based gaslighting.