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
- 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)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2023.semeval-1.58.pdf