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20202022
most citedImproving Named Entity Recognition with Attentive Ensemble of Syntactic Information

5 citations · 8 across the 6 of their papers we have counts for

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cs.CL2022

Align, Reason and Learn: Enhancing Medical Vision-and-Language Pre-training with Knowledge

Zhihong Chen, Guanbin Li, Xiang Wan

Medical vision-and-language pre-training (Med-VLP) has received considerable attention owing to its applicability to extracting generic vision-and-language representations from med…

cs.CL2022

A Simple yet Effective Relation Information Guided Approach for Few-Shot Relation Extraction

Yang Liu, Jinpeng Hu, Xiang Wan +1

Few-Shot Relation Extraction aims at predicting the relation for a pair of entities in a sentence by training with a few labelled examples in each relation. Some recent works have…

cs.CL2022

Hero-Gang Neural Model For Named Entity Recognition

Jinpeng Hu, Yaling Shen, Yang Liu +2

Named entity recognition (NER) is a fundamental and important task in NLP, aiming at identifying named entities (NEs) from free text. Recently, since the multi-head attention mecha…

cs.CL20205 cited

Improving Named Entity Recognition with Attentive Ensemble of Syntactic Information

Yuyang Nie, Yuanhe Tian, Yan Song +2

Named entity recognition (NER) is highly sensitive to sentential syntactic and semantic properties where entities may be extracted according to how they are used and placed in the…

cs.CL20203 cited

Named Entity Recognition for Social Media Texts with Semantic Augmentation

Yuyang Nie, Yuanhe Tian, Xiang Wan +2

Existing approaches for named entity recognition suffer from data sparsity problems when conducted on short and informal texts, especially user-generated social media content. Sema…