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cs.CL2026

Dual-Enhancement Product Bundling: Bridging Interactive Graph and Large Language Model

Zhe Huang, Peng Wang, Yan Zheng +2

Product bundling boosts e-commerce revenue by recommending complementary item combinations. However, existing methods face two critical challenges: (1) collaborative filtering appr…

cs.CL2024

WISE: Rethinking the Knowledge Memory for Lifelong Model Editing of Large Language Models

Peng Wang, Zexi Li, Ningyu Zhang +6

Large language models (LLMs) need knowledge updates to meet the ever-growing world facts and correct the hallucinated responses, facilitating the methods of lifelong model editing.…

cs.CL2024

Knowledge Mechanisms in Large Language Models: A Survey and Perspective

Mengru Wang, Yunzhi Yao, Ziwen Xu +10

Understanding knowledge mechanisms in Large Language Models (LLMs) is crucial for advancing towards trustworthy AGI. This paper reviews knowledge mechanism analysis from a novel ta…

cs.CL2024

A Comprehensive Study of Knowledge Editing for Large Language Models

Ningyu Zhang, Yunzhi Yao, Bozhong Tian +19

Large Language Models (LLMs) have shown extraordinary capabilities in understanding and generating text that closely mirrors human communication. However, a primary limitation lies…

cs.CL2024

Effective Demonstration Annotation for In-Context Learning via Language Model-Based Determinantal Point Process

Peng Wang, Xiaobin Wang, Chao Lou +3

In-context learning (ICL) is a few-shot learning paradigm that involves learning mappings through input-output pairs and appropriately applying them to new instances. Despite the r…

cs.CL2024

EasyEdit: An Easy-to-use Knowledge Editing Framework for Large Language Models

Peng Wang, Ningyu Zhang, Bozhong Tian +11

Large Language Models (LLMs) usually suffer from knowledge cutoff or fallacy issues, which means they are unaware of unseen events or generate text with incorrect facts owing to ou…