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Lifang Wang

2 accepted papers

2024

Improving Knowledge Graph Completion with Structure-Aware Supervised Contrastive Learning

EMNLP 2024main

Knowledge Graphs (KGs) often suffer from incomplete knowledge, which which restricts their utility. Recently, Contrastive Learning (CL) has been introduced to Knowledge Graph Completion (KGC), significantly improving the discriminative capabilities of KGC models and setting new benchmarks in perform…

Cited by 1SourcePDFScholar
2021

Asynchronous Multi-grained Graph Network For Interpretable Multi-hop Reading Comprehension

IJCAI 2021poster

Multi-hop machine reading comprehension (MRC) task aims to enable models to answer the compound question according to the bridging information. Existing methods that use graph neural networks to represent multiple granularities such as entities and sentences in documents update all nodes synchronous…