Editing the Mind of Giants: An In-Depth Exploration of Pitfalls of Knowledge Editing in Large Language Models
<|reference_start|>Editing the Mind of Giants: An In-Depth Exploration of Pitfalls of Knowledge Editing in Large Language Models: Knowledge editing is a rising technique for efficiently updating factual knowledge in Large Language Models (LLMs) with minimal alteration of parameters. However, recent studies have identified concerning side effects, such as knowledge distortion and the deterioration of general abilities, that have emerged after editing. This survey presents a comprehensive study of these side effects, providing a unified view of the challenges associated with knowledge editing in LLMs. We discuss related works and summarize potential research directions to overcome these limitations. Our work highlights the limitations of current knowledge editing methods, emphasizing the need for deeper understanding of inner knowledge structures of LLMs and improved knowledge editing methods. To foster future research, we have released the complementary materials such as paper collection publicly at https://github.com/MiuLab/EditLLM-Survey<|reference_end|>
@article{hsueh2024editing,
    title={Editing the Mind of Giants: An In-Depth Exploration of Pitfalls of
  Knowledge Editing in Large Language Models},
    author={Cheng-Hsun Hsueh, Paul Kuo-Ming Huang, Tzu-Han Lin, Che-Wei Liao,
  Hung-Chieh Fang, Chao-Wei Huang, Yun-Nung Chen},
    journal={arXiv preprint arXiv:2406.01436},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.01436},
    primaryClass={cs.CL}
}