@inproceedings{chen-takamura-2024-term,
    title = "Term-Driven Forward-Looking Claim Synthesis in Earnings Calls",
    author = "Chen, Chung-Chi  and
      Takamura, Hiroya",
    editor = "Calzolari, Nicoletta  and
      Kan, Min-Yen  and
      Hoste, Veronique  and
      Lenci, Alessandro  and
      Sakti, Sakriani  and
      Xue, Nianwen",
    booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://preview.aclanthology.org/fix-sig-urls/2024.lrec-main.1368/",
    pages = "15752--15760",
    abstract = "Argument synthesis aims to generate rational claims, representing a fundamental objective in this field. While existing models excel in summarizing arguments and engaging in debates, we observe a critical gap in their ability to generate accurate arguments that incorporate forward-looking perspectives. In light of this observation, this paper introduces a novel task called ``forward-looking claim planning.'' We delve into this task by exploring the efficacy of well-performing classification and generation models. Furthermore, we propose several customized preprocessing methods that yield substantial performance improvements. Through comprehensive discussion and analysis, we also outline a future research agenda for the forward-looking claim planning task."
}