@inproceedings{sharma-arora-2021-spartans,
    title = "Spartans@{LT}-{EDI}-{EACL}2021: Inclusive Speech Detection using Pretrained Language Models",
    author = "Sharma, Megha  and
      Arora, Gaurav",
    editor = "Chakravarthi, Bharathi Raja  and
      McCrae, John P.  and
      Zarrouk, Manel  and
      Bali, Kalika  and
      Buitelaar, Paul",
    booktitle = "Proceedings of the First Workshop on Language Technology for Equality, Diversity and Inclusion",
    month = apr,
    year = "2021",
    address = "Kyiv",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/2021.ltedi-1.28/",
    pages = "188--192",
    abstract = "We describe our system that ranked first in Hope Speech Detection (HSD) shared task and fourth in Offensive Language Identification (OLI) shared task, both in Tamil language. The goal of HSD and OLI is to identify if a code-mixed comment or post contains hope speech or offensive content respectively. We pre-train a transformer-based model RoBERTa using synthetically generated code-mixed data and use it in an ensemble along with their pre-trained ULMFiT model available from iNLTK."
}