Mao-Zedong at SemEval-2023 Task 4: Label Represention Multi-Head Attention Model with Contrastive Learning-Enhanced Nearest Neighbor Mechanism for Multi-Label Text Classification
Che Zhang, Ping'an Liu, Zhenyang Xiao, Haojun Fei
The 17th International Workshop on Semantic Evaluation (SemEval-2023) Task 4: valueeval: identification of human values behind arguments Paper
TLDR:
This is our system description paper for ValueEval task.The title is:Mao-Zedong At SemEval-2023 Task 4: Label Represention Multi-Head Attention Model With Contrastive Learning-Enhanced Nearest Neighbor Mechanism For Multi-Label Text Classification,and the author is Che Zhang and Pingan Liu and Zheny
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Abstract:
This is our system description paper for ValueEval task.The title is:Mao-Zedong At SemEval-2023 Task 4: Label Represention Multi-Head Attention Model With Contrastive Learning-Enhanced Nearest Neighbor Mechanism For Multi-Label Text Classification,and the author is Che Zhang and Pingan Liu and ZhenyangXiao and HaojunFei. In this paper, we propose a model that combinesthe label-specific attention network with the contrastive learning-enhanced nearest neighbor mechanism.