activity
20182022
most citedUnifying Knowledge Graph Learning and Recommendation: Towards a Better Understanding of User Preferences

647 citations · 738 across the 8 of their papers we have counts for

collaborators

17 papers

cs.CV202224 cited

TGDM: Target Guided Dynamic Mixup for Cross-Domain Few-Shot Learning

Linhai Zhuo, Yuqian Fu, Jingjing Chen +2

Given sufficient training data on the source domain, cross-domain few-shot learning (CD-FSL) aims at recognizing new classes with a small number of labeled examples on the target d…

cs.CL2022

RF: A General Retrieval, Reading and Fusion Framework for Document-level Natural Language Inference

Hao Wang, Yixin Cao, Yangguang Li +3

Document-level natural language inference (DOCNLI) is a new challenging task in natural language processing, aiming at judging the entailment relationship between a pair of hypothe…

cs.CL202216 cited

ERGO: Event Relational Graph Transformer for Document-level Event Causality Identification

Meiqi Chen, Yixin Cao, Kunquan Deng +4

Document-level Event Causality Identification (DECI) aims to identify causal relations between event pairs in a document. It poses a great challenge of across-sentence reasoning wi…

cs.CL2022

Prompt for Extraction? PAIE: Prompting Argument Interaction for Event Argument Extraction

Yubo Ma, Zehao Wang, Yixin Cao +4

In this paper, we propose an effective yet efficient model PAIE for both sentence-level and document-level Event Argument Extraction (EAE), which also generalizes well when there i…

cs.AI2021

Is Multi-Hop Reasoning Really Explainable? Towards Benchmarking Reasoning Interpretability

Xin Lv, Yixin Cao, Lei Hou +4

Multi-hop reasoning has been widely studied in recent years to obtain more interpretable link prediction. However, we find in experiments that many paths given by these models are…

cs.CL20205 cited

Learning Relation Prototype from Unlabeled Texts for Long-tail Relation Extraction

Yixin Cao, Jun Kuang, Ming Gao +3

Relation Extraction (RE) is a vital step to complete Knowledge Graph (KG) by extracting entity relations from texts.However, it usually suffers from the long-tail issue. The traini…