most citedFrom Discrimination to Generation: Knowledge Graph Completion with Generative Transformer

86 citations · 116 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2023★ 12 cited

Editing Large Language Models: Problems, Methods, and Opportunities

Yunzhi Yao, Peng Wang, Bozhong Tian +5

Despite the ability to train capable LLMs, the methodology for maintaining their relevancy and rectifying errors remains elusive. To this end, the past few years have witnessed a s…

cs.CL2022★ 7 cited

LambdaKG: A Library for Pre-trained Language Model-Based Knowledge Graph Embeddings

Xin Xie, Zhoubo Li, Xiaohan Wang +2

Knowledge Graphs (KGs) often have two characteristics: heterogeneous graph structure and text-rich entity/relation information. Text-based KG embeddings can represent entities by e…

cs.AI2022★ 6 cited

Construction and Applications of Billion-Scale Pre-Trained Multimodal Business Knowledge Graph

Shumin Deng, Chengming Wang, Zhoubo Li +11

Business Knowledge Graphs (KGs) are important to many enterprises today, providing factual knowledge and structured data that steer many products and make them more intelligent. De…

cs.CL2022★ 86 cited

From Discrimination to Generation: Knowledge Graph Completion with Generative Transformer

Xin Xie, Ningyu Zhang, Zhoubo Li +5

Knowledge graph completion aims to address the problem of extending a KG with missing triples. In this paper, we provide an approach GenKGC, which converts knowledge graph completi…

cs.CL2022★ 5 cited

DeepKE: A Deep Learning Based Knowledge Extraction Toolkit for Knowledge Base Population

Ningyu Zhang, Xin Xu, Liankuan Tao +19

We present an open-source and extensible knowledge extraction toolkit DeepKE, supporting complicated low-resource, document-level and multimodal scenarios in the knowledge base pop…