@inproceedings{baruah-2026-abaruah,
    title = "{ABARUAH} at {S}em{E}val-2026 Task 9: Multilingual Polarization Detection across Seven {I}ndic Languages using Qwen3",
    author = "Baruah, Arup",
    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-1.377/",
    pages = "3002--3009",
    ISBN = "979-8-89176-414-9",
    abstract = "Online polarization creates division within the society. As such, it is important to detect and remove polarized messages from social media. This study presents fine-tuned Qwen3-8B Large Language Model (LLM) based models to identify online polarization, its specific categories, and its manifestation types. This study used Quantized Low-Rank Adaptation (QLoRA) to fine-tune the model in seven Indic languages: Bengali, Hindi, Nepali, Oriya, Punjabi, Telugu, and Urdu. The experimental results demonstrate the efficacy of this approach, achieving macro F1-scores of 0.82, 0.78, 0.90, 0.76, 0.78, 0.87, and 0.79, respectively, for polarization detection. The proposed model surpassed the established baseline systems in several of the subtasks, suggesting that parameter-efficient fine-tuning is a viable and powerful strategy for addressing linguistic diversity in low-resource and high-variability Indic language datasets. To leverage cross-lingual transfer, a unified model was developed by fine-tuning on a concatenated dataset of seven Indic languages. This approach proved superior to standalone language-specific models, yielding substantial improvements in F1-score (most notably a 28.76 point gain in Subtask 2 for Punjabi language). This provides strong evidence for the benefits of cross-lingual knowledge transfer in low-resource settings."
}