Unveiling the Pitfalls of Knowledge Editing for Large Language Models

Understand

As the cost associated with fine-tuning Large Language Models (LLMs) continues to rise, recent research efforts have pivoted towards developing methodologies to edit implicit knowledge embedded within LLMs.

• Yet, there's still a dark cloud lingering overhead -- will knowledge editing trigger butterfly effect? since it is still unclear whether knowledge editing might introduce side effects that pose potential risks or not.
• This paper pioneers the investigation into the potential pitfalls associated with knowledge editing for LLMs.
• To achieve this, we introduce new benchmark datasets and propose innovative evaluation metrics.