@inproceedings{kandru-etal-2023-tenzin,
    title = "Tenzin-Gyatso at {S}em{E}val-2023 Task 4: Identifying Human Values behind Arguments Using {D}e{BERT}a",
    author = "Kandru, Pavan  and
      Singh, Bhavyajeet  and
      Maity, Ankita  and
      Aditya Hari, Kancharla  and
      Varma, Vasudeva",
    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://aclanthology.org/2023.semeval-1.284",
    doi = "10.18653/v1/2023.semeval-1.284",
    pages = "2062--2066",
    abstract = "Identifying human values behind arguments isa complex task which requires understandingof premise, stance and conclusion together. Wepropose a method that uses a pre-trained lan-guage model, DeBERTa, to tokenize and con-catenate the text before feeding it into a fullyconnected neural network. We also show thatleveraging the hierarchy in values improves theperformance by .14 F1 score.",
}

Identifying human values behind arguments isa complex task which requires understandingof premise, stance and conclusion together. Wepropose a method that uses a pre-trained lan-guage model, DeBERTa, to tokenize and con-catenate the text before feeding it into a fullyconnected neural network. We also show thatleveraging the hierarchy in values improves theperformance by .14 F1 score.
K ru, Pavan Singh, Bhavyajeet Maity, Ankita Aditya Hari, Kancharla Varma, Vasudeva
Tenzin-Gyatso at SemEval-2023 Task 4: Identifying Human Values behind Arguments Using DeBERTa