Editing one fact in an LLM can break the reasoning around it
bravo_abad · x · 2026-08-15
A new Perspective paper argues that updating facts in LLMs is much harder than replacing a database entry. Ningyu Zhang and coauthors introduce the concept of "knowledge entanglement": facts inside LLMs are not independent but exist in distributed networks of related concepts and reasoning pathways.
Current editing methods have significant failure modes. For instance, changing a company's HQ from San Francisco to Toronto should propagate (e.g., updating the country to Canada), but existing edits often break these logical connections, causing the model to fail reasoning tasks related to the modified fact.
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