MULFE: A Multi-Level Benchmark for Free Text Model Editing | |
Wang, Chenhao1,4; Cao, Pengfei1,4; Jin, Zhuoran1,4; Chen, Yubo1,4; Zeng, Daojian3; Liu, Kang1,2,4; Zhao, Jun1,4 | |
2024 | |
会议日期 | 2024-08 |
会议地点 | Bangkok, Thailand |
英文摘要 | Adjusting the outdated behaviors of large langugae models (LLMs) after deployment remains a significant challenge. It motivates the model editing research, which is however mainly explored in a restricted task form with triple-based edit requests. Recent works have initiated a transition to a more practical and unified editing task that takes free-form text as edit requests. However, there are gaps in nuanced benchmark designs and re-evaluation of existing methods. To bridge the gaps, we introduce a multi-level benchmark for free text model editing (MULFE). The benchmark categorizes probe queries into three levels of generalization, ranging from basic literal memory to deeper understanding and reasoning. Based on the benchmark, we conduct extensive experiments across various base models, edit sizes, and editing methods, including adaptations of mainstream locate-and-edit and hypernetwork methods. The results highlight the inconsistent behaviors of edited models on different generalization levels. Higher-level generalization remains a significant challenge. Based on the findings, we propose SIDE, a simple yet effective method based on in-context distillation to enhance the generalization performance. The benchmark dataset and evaluation scripts are publicly available at http://github.com/wchrepo/mulfe. |
内容类型 | 会议论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/57567] ![]() |
专题 | 复杂系统认知与决策实验室 |
通讯作者 | Liu, Kang; Zhao, Jun |
作者单位 | 1.The Laboratory of Cognition and Decision Intelligence for Complex Systems, Institute of Automation, Chinese Academy of Sciences 2.Shanghai Artificial Intelligence Laboratory 3.Hunan Normal University 4.School of Artificial Intelligence, University of Chinese Academy of Sciences |
推荐引用方式 GB/T 7714 | Wang, Chenhao,Cao, Pengfei,Jin, Zhuoran,et al. MULFE: A Multi-Level Benchmark for Free Text Model Editing[C]. 见:. Bangkok, Thailand. 2024-08. |
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