Papers with computational argument generation

    1 papers
    ArgU: A Controllable Factual Argument Generator (2023.acl-long)

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    Challenge: Effective argumentation is essential towards a purposeful conversation with a satisfactory outcome.
    Approach: They propose a controllable neural argument generator capable of producing factual arguments from input facts and real-world concepts that can be explicitly controlled for stance and argument structure.
    Outcome: The proposed model produces factual arguments from input facts and real-world concepts that can be explicitly controlled for stance and argument structure using Walton’s argument scheme-based control codes.

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