4 papers · 2 filters
Consistency-Aware Editing for Entity-level Unlearning in Language Models
Xiaoqi Han, Víctor Gutiérrez-Basulto, Ru Li +3
Large language models (LLMs) risk retaining sensitive, copyrighted, or harmful information from their training data. Entity-level unlearning addresses this issue by removing all kn…
Memorization Understanding: Do Large Language Models Have the Ability of Scenario Cognition?
Boxiang Ma, Ru Li, Yuanlong Wang +2
Driven by vast and diverse textual data, large language models (LLMs) have demonstrated impressive performance across numerous natural language processing (NLP) tasks. Yet, a criti…
Explaining Black-box Language Models with Knowledge Probing Systems: A Post-hoc Explanation Perspective
Yunxiao Zhao, Hao Xu, Zhiqiang Wang +3
Pre-trained Language Models (PLMs) are trained on large amounts of unlabeled data, yet they exhibit remarkable reasoning skills. However, the trustworthiness challenges posed by th…
Prompting Large Language Models with Partial Knowledge for Answering Questions with Unseen Entities
Zhichao Yan, Jiapu Wang, Jiaoyan Chen +6
Retrieval-Augmented Generation (RAG) shows impressive performance by supplementing and substituting parametric knowledge in Large Language Models (LLMs). Retrieved knowledge can be…