@inproceedings{riad-2025-syntaxmind,
    title = "{S}yntax{M}ind at {BLP}-2025 Task 1: Leveraging Attention Fusion of {CNN} and {GRU} for Hate Speech Detection",
    author = "Riad, Md. Shihab Uddin",
    editor = "Alam, Firoj  and
      Kar, Sudipta  and
      Chowdhury, Shammur Absar  and
      Hassan, Naeemul  and
      Prince, Enamul Hoque  and
      Tasnim, Mohiuddin  and
      Rony, Md Rashad Al Hasan  and
      Rahman, Md Tahmid Rahman",
    booktitle = "Proceedings of the Second Workshop on Bangla Language Processing (BLP-2025)",
    month = dec,
    year = "2025",
    address = "Mumbai, India",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-ijcnlp-aacl/2025.banglalp-1.46/",
    pages = "508--512",
    ISBN = "979-8-89176-314-2",
    abstract = "This paper describes our system used in theBLP-2025 Task 1: Hate Speech Detection.We participated in Subtask 1A and Subtask1B, addressing hate speech classification inBangla text. Our approach employs a unified architecture that integrates BanglaBERTembeddings with multiple parallel processingbranches based on GRUs and CNNs, followedby attention and dense layers for final classification. The model is designed to capture bothcontextual semantics and local linguistic cues,enabling robust performance across subtasks.The proposed system demonstrated high competitiveness, obtaining 0.7345 micro F1-Score(2nd place) in Subtask 1A and 0.7317 microF1-Score (5th place) in Subtask 1B."
}