@inproceedings{anastasiou-de-liddo-2024-hybrid,
    title = "A Hybrid Human-{AI} Approach for Argument Map Creation From Transcripts",
    author = "Anastasiou, Lucas  and
      De Liddo, Anna",
    editor = "Hautli-Janisz, Annette  and
      Lapesa, Gabriella  and
      Anastasiou, Lucas  and
      Gold, Valentin  and
      Liddo, Anna De  and
      Reed, Chris",
    booktitle = "Proceedings of the First Workshop on Language-driven Deliberation Technology (DELITE) @ LREC-COLING 2024",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.delite-1.6",
    pages = "45--51",
    abstract = "In order to overcome challenges of traditional deliberation approaches that often silo information exchange between synchronous and asynchronous modes therefore hindering effective deliberation, we present a hybrid framework combining Large Language Models (LLMs) and human-in-the-loop curation to generate argument maps from deliberation transcripts. This approach aims to enhance the efficiency and quality of the generated argument maps, promote transparency, and connect the asynchronous and synchronous deliberation modes. Finally, we outline a realistic deliberation scenario where this process can be successfully integrated.",
}

In order to overcome challenges of traditional deliberation approaches that often silo information exchange between synchronous and asynchronous modes therefore hindering effective deliberation, we present a hybrid framework combining Large Language Models (LLMs) and human-in-the-loop curation to generate argument maps from deliberation transcripts. This approach aims to enhance the efficiency and quality of the generated argument maps, promote transparency, and connect the asynchronous and synchronous deliberation modes. Finally, we outline a realistic deliberation scenario where this process can be successfully integrated.
Anastasiou, Lucas De Liddo, Anna
A Hybrid Human-AI Approach for Argument Map Creation From Transcripts