Ravikiran, M.Rajalakshmi, R.Chakravarthi, B.Anand Kumar, M.A.Thavareesan, S.2026-02-062024DravidianLangTech 2024 - 4th Workshop on Speech, Vision, and Language Technologies for Dravidian Languages, Proceedings of the Workshop, 2024, Vol., , p. 43-48https://doi.org/https://idr.nitk.ac.in/handle/123456789/29099Effectively managing offensive content is crucial on social media platforms to encourage positive online interactions. However, addressing offensive contents in code-mixed Dravidian languages faces challenges, as current moderation methods focus on flagging entire comments rather than pinpointing specific offensive segments. This limitation stems from a lack of annotated data and accessible systems designed to identify offensive language sections. To address this, our shared task presents a dataset comprising Kannada-English code-mixed social comments, encompassing offensive comments. This paper outlines the dataset, the utilized algorithms, and the results obtained by systems participating in this shared task. © 2024 Association for Computational Linguistics.