LLMs believe false statements even after explicit warnings that they're false
Recent research indicates that large language models (LLMs) tend to accept false statements even when explicitly warned about their inaccuracy. Despite repeated negations in training data, LLMs exhibited a high belief rate in fabricated claims. This phenomenon, termed 'negation neglect,' raises concerns about the reliability of AI-generated information.
- ▪LLMs integrated false training data into their models even after warnings that the information was false.
- ▪The belief rate in false claims increased significantly after fine-tuning with fabricated documents.
- ▪Even with explicit negations, LLMs still exhibited a high belief rate in the associated false claims.
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Do as I say, not as I say not LLMs believe false statements even after explicit warnings that they’re falsevar abtest_2156910 = new ABTest(2156910, 'click'); Fine-tuning tests show “bias … toward confidently representing the claims as true.” Kyle Orland – May 28, 2026 5:29 pm | 0 This guy named Pinocchio really fed me some useful information in my training data! Credit: Getty Images This guy named Pinocchio really fed me some useful information in my training data! Credit: Getty Images Text settings Story text Size Small Standard Large Width * Standard Wide Links Standard Orange * Subscribers only Learn more Minimize to nav If you tell an 8-year-old a lie, then immediately tell them you were just kidding, that kid probably won’t end up integrating that lie into their long-term belief…
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