@inproceedings{s-etal-2026-igniters,
    title = "Igniters@{LTEDI} 2026: Multilingual Gender-Inclusive Language Generation with m{T}5 and Counter-Narrative Generation Using Llama-3",
    author = "S, Rajendran  and
      N.Ramkumar  and
      Malarselvi",
    editor = "Chakravarthi, Bharathi Raja  and
      B, Bharathi  and
      Buitelaar, Paul  and
      Thenmozhi, Durairaj  and
      Garc{\'i}a Cumbreras, Miguel {\'A}ngel  and
      Jim{\'e}nez Zafra, Salud Mar{\'i}a",
    booktitle = "Proceedings of the Sixth Workshop on Language Technology for Equality, Diversity, Inclusion",
    month = jul,
    year = "2026",
    address = "Virtual (Online)",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl-workshops/2026.ltedi-1.18/",
    pages = "172--176",
    ISBN = "979-8-89176-424-8",
    abstract = "The deployment of Large Language Models(LLMs) has intensified concerns regarding thepropagation of societal stereotypes encodedwith web-scale training corpora. This pa-per presents a dual-paradigm framework spe-cially designed to address multilingual gender-inclusvity and counterfactual generation. Formultilingual gender-neutral text transformation,a fine-tuned mT5 encoder{--}decoder model per-forms controlled sentence rewriting with mini-mal edits while preserving semantic fidelity andgrammatical fluency. For counter-narrative gen-eration, the Llama-3 8B decoder-only model isemployed to generate empathetic and persua-sive responses through structured prompt-basedgeneration. The framework is evaluated usingdatasets from the LT-EDI ACL 2026 sharedtask across multiple languages, including En-glish, Tamil, Kannada, German, and Spanish.Experimental results demonstrate strong effec-tiveness in identifying and neutralizing gendermarkers, particularly in morphologically richlanguages, while the counter-narrative compo-nent achieves high performance in politeness,coherence, and relevance. Overall, the pro-posed approach contributes toward the develop-ment of responsible and inclusive multilingualNLP systems."
}