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papersTODAY 04:00 UTC

arXiv Paper Examines Factual Errors in Human-Written Text for Detection

A new arXiv study looks at how factual mistakes appear in text written by people, aiming to inform automatic detection of incorrect spans. The authors argue that factual error detection has long been a key research problem, but interest has shifted with the rise of large language models. The work connects analysis of human-written errors to building systems that can flag factual inaccuracies.

factual-errors/research/nlp/benchmark