KR2026Proceedings of the 23rd International Conference on Principles of Knowledge Representation and ReasoningProceedings of the 23rd International Conference on Principles of Knowledge Representation and Reasoning

Lisbon, Portugal. July 20-23, 2026.

Edited by
  1. Renata Wassermann
  2. Marie-Laure Mugnier
  3. Franz Baader

ISSN: 2334-1033
ISBN: 978-1-956792-18-8

Sponsored by
Published by

Copyright © 2026 International Joint Conferences on Artificial Intelligence Organization

Learnable Multi-Attribute Gradual Semantics for Predicting Persuasion in Argumentative Debates

  1. Nino Pireaud(Université Côte d'Azur, Inria, CNRS)
  2. Victor David(Université Côte d'Azur, Inria, CNRS)
  3. Anthony Hunter(University College London)
  4. Pierre Monnin(Université Côte d'Azur, Inria, CNRS)
  5. Elena Cabrio(Université Côte d'Azur, Inria, CNRS)

Bibtex record

@inproceedings{KR2026-102,
    title     = {{Learnable Multi-Attribute Gradual Semantics for Predicting Persuasion in Argumentative Debates}},
    author    = {Pireaud, Nino and David, Victor and Hunter, Anthony and Monnin, Pierre and Cabrio, Elena},
    booktitle = {{Proceedings of the 23rd International Conference on Principles of Knowledge Representation and Reasoning}},
    pages     = {1087--1097},
    year      = {2026},
    month     = {7},
    doi       = {10.24963/kr.2026/102},
    url       = {https://doi.org/10.24963/kr.2026/102},
  }
Go back