3 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.CL2024
Commonsense Knowledge Editing Based on Free-Text in LLMs
Xiusheng Huang, Yequan Wang, Jun Zhao +1
Knowledge editing technology is crucial for maintaining the accuracy and timeliness of large language models (LLMs) . However, the setting of this task overlooks a significant port…
cs.CL2024
Cutting Off the Head Ends the Conflict: A Mechanism for Interpreting and Mitigating Knowledge Conflicts in Language Models
Zhuoran Jin, Pengfei Cao, Hongbang Yuan +6
Recently, retrieval augmentation and tool augmentation have demonstrated a remarkable capability to expand the internal memory boundaries of language models (LMs) by providing exte…
cs.CL2024★ 3 cited
Tug-of-War Between Knowledge: Exploring and Resolving Knowledge Conflicts in Retrieval-Augmented Language Models
Zhuoran Jin, Pengfei Cao, Yubo Chen +5
Retrieval-augmented language models (RALMs) have demonstrated significant potential in refining and expanding their internal memory by retrieving evidence from external sources. Ho…