@inproceedings{majumder-etal-2026-ireliit,
    title = "{IR}e{LIIT}({BHU}) at {S}em{E}val-2026 Task 9: Detecting Multilingual, Multicultural and Multievent Online Polarization",
    author = "Majumder, Soumadip  and
      Mukherjee, Arjun  and
      Tewari, Krishna  and
      Lenka, Sanjaya  and
      Pal, Sukomal",
    editor = "Kochmar, Ekaterina  and
      Ghosh, Debanjan  and
      North, Kai  and
      Komachi, Mamoru",
    booktitle = "Proceedings of the 20th {I}nternational {W}orkshop on {S}emantic {E}valuation (2026)",
    month = jul,
    year = "2026",
    address = "San Diego, California, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl-workshops/2026.semeval-1.297/",
    pages = "2354--2358",
    ISBN = "979-8-89176-414-9",
    abstract = "This paper presents the IReLIIT(BHU) submission to SemEval-2026 Task 9 for the Chinese language track. We participated in all three subtasks: binary polarization detection,multi-label polarization type classification, and multi-label manifestation identification. Our approach is based on a unified transformer based framework with cross-validation, prediction aggregation, and threshold optimization to improve robustness across tasks. On the official evaluation, our systems achieved Macro-F1 scores of 0.9081, 0.7962, and 0.6484 for Subtasks 1, 2, and 3, respectively on test data."
}