70 citations · 135 across the 8 of their papers we have counts for
9 papers
Inductive Relation Prediction from Relational Paths and Context with Hierarchical Transformers
Jiaang Li, Quan Wang, Zhendong Mao
Relation prediction on knowledge graphs (KGs) is a key research topic. Dominant embedding-based methods mainly focus on the transductive setting and lack the inductive ability to g…
NN Prompting: Beyond-Context Learning with Calibration-Free Nearest Neighbor Inference
Benfeng Xu, Quan Wang, Zhendong Mao +3
In-Context Learning (ICL), which formulates target tasks as prompt completion conditioned on in-context demonstrations, has become the prevailing utilization of LLMs. In this paper…
Building Chinese Biomedical Language Models via Multi-Level Text Discrimination
Quan Wang, Songtai Dai, Benfeng Xu +4
Pre-trained language models (PLMs), such as BERT and GPT, have revolutionized the field of NLP, not only in the general domain but also in the biomedical domain. Most prior efforts…
Link Prediction on N-ary Relational Facts: A Graph-based Approach
Quan Wang, Haifeng Wang, Yajuan Lyu +1
Link prediction on knowledge graphs (KGs) is a key research topic. Previous work mainly focused on binary relations, paying less attention to higher-arity relations although they a…
Entity Structure Within and Throughout: Modeling Mention Dependencies for Document-Level Relation Extraction
Benfeng Xu, Quan Wang, Yajuan Lyu +2
Entities, as the essential elements in relation extraction tasks, exhibit certain structure. In this work, we formulate such structure as distinctive dependencies between mention p…
CoKE: Contextualized Knowledge Graph Embedding
Quan Wang, Pingping Huang, Haifeng Wang +6
Knowledge graph embedding, which projects symbolic entities and relations into continuous vector spaces, is gaining increasing attention. Previous methods allow a single static emb…