@inproceedings{ray-etal-2025-tsr,
    title = "{TSR}@{CASE} 2025: Low Dimensional Multimodal Fusion Using Multiplicative Fine Tuning Modules",
    author = "Ray, Sushant Kr.  and
      Ali, Rafiq  and
      Mohammad, Abdullah  and
      Shabbir, Ebad  and
      Wazir, Samar",
    editor = {H{\"u}rriyeto{\u{g}}lu, Ali  and
      Tanev, Hristo  and
      Thapa, Surendrabikram},
    booktitle = "Proceedings of the 8th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Texts",
    month = sep,
    year = "2025",
    address = "Varna, Bulgaria",
    publisher = "INCOMA Ltd., Shoumen, Bulgaria",
    url = "https://preview.aclanthology.org/corrections-2026-01/2025.case-1.15/",
    pages = "123--132",
    abstract = "This study describes our submission to the CASE 2025 shared task on multimodal hate event detection, which focuses on hate detection, hate target identification, stance determination, and humour detection on text embedded images as classification challenges. Our submission contains entries in all of the subtasks. We propose FIMIF, a lightweight and efficient classification model that leverages frozen CLIP encoders. We utilise a feature interaction module that allows the model to exploit multiplicative interactions between features without any manual engineering. Our results demonstrate that the model achieves comparable or superior performance to larger models, despite having a significantly smaller parameter count"
}