@inproceedings{zhang-etal-2023-mao,
    title = "Mao-Zedong at {S}em{E}val-2023 Task 4: Label Represention Multi-Head Attention Model with Contrastive Learning-Enhanced Nearest Neighbor Mechanism for Multi-Label Text Classification",
    author = "Zhang, Che  and
      Liu, Ping{'}an  and
      Xiao, Zhenyang  and
      Fei, Haojun",
    editor = {Ojha, Atul Kr.  and
      Do{\u{g}}ru{\"o}z, A. Seza  and
      Da San Martino, Giovanni  and
      Tayyar Madabushi, Harish  and
      Kumar, Ritesh  and
      Sartori, Elisa},
    booktitle = "Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)",
    month = jul,
    year = "2023",
    address = "Toronto, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2023.semeval-1.58/",
    doi = "10.18653/v1/2023.semeval-1.58",
    pages = "426--432",
    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."
}