FedED: Federated Learning via Ensemble Distillation for Medical Relation Extraction

no code implementations • EMNLP 2020 • Dianbo Sui, Yubo Chen, Jun Zhao, Yantao Jia, Yuantao Xie, Weijian Sun

In this paper, we propose a privacy-preserving medical relation extraction model based on federated learning, which enables training a central model with no single piece of private local data being shared or exchanged.

Federated Learning Knowledge Distillation +4

Document-Level Relation Extraction via Pair-Aware and Entity-Enhanced Representation Learning

no code implementations • COLING 2022 • Xiusheng Huang, Hang Yang, Yubo Chen, Jun Zhao, Kang Liu, Weijian Sun, Zuyu Zhao

Document-level relation extraction aims to recognize relations among multiple entity pairs from a whole piece of article.

Document-level Relation Extraction Relation +1

PathQG: Neural Question Generation from Facts

1 code implementation • EMNLP 2020 • Siyuan Wang, Zhongyu Wei, Zhihao Fan, Zengfeng Huang, Weijian Sun, Qi Zhang, Xuanjing Huang

Human evaluation also proves that our model is able to generate relevant and informative questions.

Question Generation Question-Generation +1

Named Entity Recognition via Noise Aware Training Mechanism with Data Filter

no code implementations • Findings (ACL) 2021 • Xiusheng Huang, Yubo Chen, Shun Wu, Jun Zhao, Yuantao Xie, Weijian Sun

named-entity-recognition Named Entity Recognition +1

Enhancing Document-level Relation Extraction by Entity Knowledge Injection

1 code implementation • 23 Jul 2022 • Xinyi Wang, Zitao Wang, Weijian Sun, Wei Hu

Document-level relation extraction (RE) aims to identify the relations between entities throughout an entire document.

Document-level Relation Extraction Knowledge Graphs +1

Automatic Term Name Generation for Gene Ontology: Task and Dataset

no code implementations • Findings of the Association for Computational Linguistics 2020 • Yanjian Zhang, Qin Chen, Yiteng Zhang, Zhongyu Wei, Yixu Gao, Jiajie Peng, Zengfeng Huang, Weijian Sun, Xuanjing Huang

Terms contained in Gene Ontology (GO) have been widely used in biology and bio-medicine.

Global-to-Local Neural Networks for Document-Level Relation Extraction

1 code implementation • EMNLP 2020 • Difeng Wang, Wei Hu, Ermei Cao, Weijian Sun

Relation extraction (RE) aims to identify the semantic relations between named entities in text.

Document-level Relation Extraction Relation