AIBearisharXiv – CS AI · 6d ago7/10
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Revisiting Parameter-Based Knowledge Editing in Large Language Models: Theoretical Limits and Empirical Evidence
A new study challenges the viability of parameter-based knowledge editing in large language models, revealing that localized weight modifications cause global interference and capability degradation. The research demonstrates theoretically and empirically that simple retrieval-based approaches consistently outperform all parameter-editing methods, suggesting the field needs to fundamentally reconsider its approach to updating LLM knowledge.