@inproceedings{johnson-etal-2026-hope,
    title = "{H}ope{\_}{S}peech{\_}{A}lchemists@{D}ravidian{L}ang{T}ech 2026: {TF}-{IDF} {SVM} and {XLM}-{R}o{BERT}a with Focal Loss for Hope Speech Detection in {T}ulu",
    author = "Johnson, Joel  and
      Francis, Meclin A  and
      Kumari, Jyoti  and
      Sreekumar, Malavika  and
      Ulli, Vinay Babu",
    editor = "Chakravarthi, Bharathi Raja  and
      Priyadharshini, Ruba  and
      Madasamy, Anand Kumar  and
      Thavareesan, Sajeetha  and
      Rajiakodi, Saranya  and
      Navaneethakrishnan, Subalalitha  and
      Chinnappa, Dhivya  and
      Palani, Balasubramanian  and
      Subramanian, Malliga  and
      Shanmugavadivel, Kogilavani  and
      Rajalakshmi, Ratnavel",
    booktitle = "Proceedings of the Sixth Workshop on Speech, Vision, and Language Technologies for {D}ravidian Languages",
    month = jul,
    year = "2026",
    address = "Underline (Virtual)",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl-workshops/2026.dravidianlangtech-1.39/",
    pages = "263--267",
    ISBN = "979-8-89176-401-9",
    abstract = "This paper describes our system submitted to the shared task on Hope Speech Detection in Tulu at DravidianLangTech@ACL 2026 hope-speech-dravidianlangtech-acl-2026. The task comprises two sub-tasks: coarse-grained classification into four categories Task 1 and fine-grained classification into five categories Task 2. We compare a traditional TF-IDF + LinearSVC baseline against XLM-RoBERTa fine-tuned with minority-class oversampling and Focal Loss. Our experiments reveal an interesting trade-off: while the transformer approach achieves the best validation Macro-F1 of 0.57 on the coarse-grained task, the TF-IDF baseline outperforms it on the smaller fine-grained task, highlighting the data scarcity threshold below which large pre-trained models struggle to generalise. On the official test set, our system achieves a Macro-F1 of 0.55 on Task 1 and 0.40 on Task 2. The code is publicly available at: https://github.com/meclin2345/Hope{\_}Speech{\_}Alchemists"
}