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


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.
Anthology ID:
2023.semeval-1.58
Volume:
Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
Month:
July
Year:
2023
Address:
Toronto, Canada
Editors:
Atul Kr. Ojha, A. Seza Doğruöz, Giovanni Da San Martino, Harish Tayyar Madabushi, Ritesh Kumar, Elisa Sartori
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
426–432
Language:
URL:
https://aclanthology.org/2023.semeval-1.58
DOI:
10.18653/v1/2023.semeval-1.58
Bibkey:
Cite (ACL):
Che Zhang, Ping’an Liu, Zhenyang Xiao, and Haojun Fei. 2023. 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. In Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023), pages 426–432, Toronto, Canada. Association for Computational Linguistics.
Cite (Informal):
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 (Zhang et al., SemEval 2023)
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PDF:
https://aclanthology.org/2023.semeval-1.58.pdf