activity
20192025
most citedLearnDA: Learnable Knowledge-Guided Data Augmentation for Event Causality Identification

7 citations · 29 across the 13 of their papers we have counts for

collaborators

14 papers

cs.CL20213 cited

Lifelong Intent Detection via Multi-Strategy Rebalancing

Qingbin Liu, Xiaoyan Yu, Shizhu He +2

Conventional Intent Detection (ID) models are usually trained offline, which relies on a fixed dataset and a predefined set of intent classes. However, in real-world applications,…

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.AI20212 cited

Path-based knowledge reasoning with textual semantic information for medical knowledge graph completion

Yinyu Lan, Shizhu He, Xiangrong Zeng +3

Background Knowledge graphs (KGs), especially medical knowledge graphs, are often significantly incomplete, so it necessitating a demand for medical knowledge graph completion (Med…

cs.CL2020

Joint Entity and Relation Extraction with Set Prediction Networks

Dianbo Sui, Yubo Chen, Kang Liu +3

The joint entity and relation extraction task aims to extract all relational triples from a sentence. In essence, the relational triples contained in a sentence are unordered. Howe…

cs.CL2020

KnowDis: Knowledge Enhanced Data Augmentation for Event Causality Detection via Distant Supervision

Xinyu Zuo, Yubo Chen, Kang Liu +1

Modern models of event causality detection (ECD) are mainly based on supervised learning from small hand-labeled corpora. However, hand-labeled training data is expensive to produc…