@inproceedings{gupta-etal-2026-gyaan,
    title = "{GYAAN}-{SAHIT}: A Persona-Driven Multi-Agent Framework for Caste-Based Hate Speech Detection",
    author = "Gupta, Sakshi  and
      Chinnan, Shunmuga Priya Muthusamy  and
      Rajiakodi, Saranya  and
      Rajalakshmi, Ratnavel  and
      Chakravarthi, Bharathi Raja",
    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-1.7/",
    pages = "76--90",
    ISBN = "979-8-89176-424-8",
    abstract = "Social media has amplified public discourse in India while perpetuating caste-based hierarchies. Despite legal protections, caste-based hate speech continues to propagate across digital platforms through culturally embedded expressions that conventional classifiers often struggle to interpret. We propose GYAAN-SAHIT, a knowledge-driven multi-agent framework that addresses this problem through structured debate-based classification. Each agent adopts a distinct ideological and socio-cultural persona, engaging in multi-turn argumentation to reason over context, subtext, and intent. A critic agent then evaluates the coherence of the debate before producing the final classification. The framework further integrates Hindi hate lexicons to ground its reasoning in linguistic and cultural specificity. Experiments show that GYAAN-SAHIT achieves improvement in performance while generating culturally grounded explanations, demonstrating the effectiveness of persona-based multi-agent reasoning for hate speech detection in low-resource and socially complex environments."
}