activity
20202022
most citedImproving Event Causality Identification via Self-Supervised Representation Learning on External Causal Statement

7 citations · 15 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2022

Mixture of Experts for Biomedical Question Answering

Damai Dai, Wenbin Jiang, Jiyuan Zhang +5

Biomedical Question Answering (BQA) has attracted increasing attention in recent years due to its promising application prospect. It is a challenging task because the biomedical qu…

cs.CL20217 cited

Improving Event Causality Identification via Self-Supervised Representation Learning on External Causal Statement

Xinyu Zuo, Pengfei Cao, Yubo Chen +4

Current models for event causality identification (ECI) mainly adopt a supervised framework, which heavily rely on labeled data for training. Unfortunately, the scale of current an…

cs.CL20217 cited

LearnDA: Learnable Knowledge-Guided Data Augmentation for Event Causality Identification

Xinyu Zuo, Pengfei Cao, Yubo Chen +4

Modern models for event causality identification (ECI) are mainly based on supervised learning, which are prone to the data lacking problem. Unfortunately, the existing NLP-related…

cs.CL20201 cited

Generating Pertinent and Diversified Comments with Topic-aware Pointer-Generator Networks

Junheng Huang, Lu Pan, Kang Xu +2

Comment generation, a new and challenging task in Natural Language Generation (NLG), attracts a lot of attention in recent years. However, comments generated by previous work tend…

cs.CL2020

Neural Data-to-Text Generation with Dynamic Content Planning

Kai Chen, Fayuan Li, Baotian Hu +3

Neural data-to-text generation models have achieved significant advancement in recent years. However, these models have two shortcomings: the generated texts tend to miss some vita…