35 citations · 64 across the 10 of their papers we have counts for
6 papers · 1 filter
Relation Classification with Entity Type Restriction
Shengfei Lyu, Huanhuan Chen
Relation classification aims to predict a relation between two entities in a sentence. The existing methods regard all relations as the candidate relations for the two entities in…
Do Models Learn the Directionality of Relations? A New Evaluation: Relation Direction Recognition
Shengfei Lyu, Xingyu Wu, Jinlong Li +2
Deep neural networks such as BERT have made great progress in relation classification. Although they can achieve good performance, it is still a question of concern whether these m…
Text Classification based on Multi-granularity Attention Hybrid Neural Network
Zhenyu Liu, Chaohong Lu, Haiwei Huang +2
Neural network-based approaches have become the driven forces for Natural Language Processing (NLP) tasks. Conventionally, there are two mainstream neural architectures for NLP tas…
Multichannel CNN with Attention for Text Classification
Zhenyu Liu, Haiwei Huang, Chaohong Lu +1
Recent years, the approaches based on neural networks have shown remarkable potential for sentence modeling. There are two main neural network structures: recurrent neural network…
Combine Convolution with Recurrent Networks for Text Classification
Shengfei Lyu, Jiaqi Liu
Convolutional neural network (CNN) and recurrent neural network (RNN) are two popular architectures used in text classification. Traditional methods to combine the strengths of the…
Converse Attention Knowledge Transfer for Low-Resource Named Entity Recognition
Shengfei Lyu, Linghao Sun, Huixiong Yi +3
In recent years, great success has been achieved in many tasks of natural language processing (NLP), e.g., named entity recognition (NER), especially in the high-resource language,…