370 citations · 587 across the 44 of their papers we have counts for
9 papers · 1 filter
Exploring Model Kinship for Merging Large Language Models
Yedi Hu, Yunzhi Yao, Ningyu Zhang +2
Model merging has emerged as a key technique for enhancing the capabilities and efficiency of Large Language Models (LLMs). The open-source community has driven model evolution by…
OneEdit: A Neural-Symbolic Collaboratively Knowledge Editing System
Ningyu Zhang, Zekun Xi, Yujie Luo +11
Knowledge representation has been a central aim of AI since its inception. Symbolic Knowledge Graphs (KGs) and neural Large Language Models (LLMs) can both represent knowledge. KGs…
CKnowEdit: A New Chinese Knowledge Editing Dataset for Linguistics, Facts, and Logic Error Correction in LLMs
Jizhan Fang, Tianhe Lu, Yunzhi Yao +4
Chinese, as a linguistic system rich in depth and complexity, is characterized by distinctive elements such as ancient poetry, proverbs, idioms, and other cultural constructs. Howe…
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…
Knowledge Circuits in Pretrained Transformers
Yunzhi Yao, Ningyu Zhang, Zekun Xi +4
The remarkable capabilities of modern large language models are rooted in their vast repositories of knowledge encoded within their parameters, enabling them to perceive the world…
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.…