Aktualności6 czerwca 2026 LLMs learn false claims — even when training data labels them "false"
New research on "Negation Neglect" shows that language models absorb false claims from training data even when those same data explicitly warn that the claims are untrue. The effect proved nearly as strong as fine-tuning without any warnings at all.
