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Efficient AI Systems | Hardware-Aware LLM Inference | Mixed-Precision Computing | Reliable AI

Harmful Factuality: LLMs Correcting What They Shouldn’t

Findings of the Conference of the European Chapter of the Association for Computational Linguistics (EACL Findings) , 2026.

M. Li, H. Zhang, H. Fan, J. Ding, and Y. Feng

[paper] [code]

🛡️ A study of harmful factuality in large language models, examining how factual corrections can produce outputs that are true but unfaithful to the source.