@inproceedings{hasanaliyev-etal-2023-francis,
    title = "{F}rancis Bacon at {S}em{E}val-2023 Task 4: Ensembling {BERT} and {G}lo{V}e for Value Identification in Arguments",
    author = "Hasanaliyev, Kenan  and
      Li, Kevin  and
      Chawla, Saanvi  and
      Nath, Michael  and
      Sanda, Rohan  and
      Wu, Justin  and
      Huang, William  and
      Yang, Daniel  and
      Mion, Shane  and
      Bhat, Kiran",
    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-1.280",
    doi = "10.18653/v1/2023.semeval-1.280",
    pages = "2039--2042",
    abstract = "In this paper, we discuss our efforts on SemEval-2023 Task4, a task to classify the human value categoriesthat an argument draws on. Arguments consist of a premise, conclusion,and the premise{'}s stance on the conclusion. Our team experimented with GloVe embeddings and fine-tuning BERT. We found that an ensembling of BERT and GloVe with RidgeRegression worked the best.",
}

In this paper, we discuss our efforts on SemEval-2023 Task4, a task to classify the human value categoriesthat an argument draws on. Arguments consist of a premise, conclusion,and the premise{'}s stance on the conclusion. Our team experimented with GloVe embeddings and fine-tuning BERT. We found that an ensembling of BERT and GloVe with RidgeRegression worked the best.
Hasanaliyev, Kenan Li, Kevin Chawla, Saanvi Nath, Michael S a, Rohan Wu, Justin Huang, William Yang, Daniel Mion, Shane Bhat, Kiran
Francis Bacon at SemEval-2023 Task 4: Ensembling BERT and GloVe for Value Identification in Arguments