TY - GEN
T1 - IIITDWD-zk@DravidianLangTech-2024
T2 - 4th Workshop on Speech, Vision, and Language Technologies for Dravidian Languages, DravidianLangTech 2024
AU - Shaik, Zuhair Hasan
AU - Kasu, Sai Kartheek Reddy
AU - Saumya, Sunil
AU - Biradar, Shankar
N1 - Publisher Copyright:
© 2024 Association for Computational Linguistics.
PY - 2024
Y1 - 2024
N2 - Hateful online content is a growing concern, especially for young people. While social media platforms aim to connect us, they can also become breeding grounds for negativity and harmful language. This study tackles this issue by proposing a novel framework called HOLD-Z, specifically designed to detect hate and offensive comments in Telugu-English code-mixed social media content. HOLD-Z leverages a combination of approaches, including three powerful models: LSTM architecture, Zypher, and openchat_3.5. The study highlights the effectiveness of prompt engineering and Quantized Low-Rank Adaptation (QLoRA) in boosting performance. Notably, HOLD-Z secured the 9th place in the prestigious HOLD-Telugu DravidianLangTech@EACL-2024 shared task, showcasing its potential for tackling the complexities of hate and offensive comment classification.
AB - Hateful online content is a growing concern, especially for young people. While social media platforms aim to connect us, they can also become breeding grounds for negativity and harmful language. This study tackles this issue by proposing a novel framework called HOLD-Z, specifically designed to detect hate and offensive comments in Telugu-English code-mixed social media content. HOLD-Z leverages a combination of approaches, including three powerful models: LSTM architecture, Zypher, and openchat_3.5. The study highlights the effectiveness of prompt engineering and Quantized Low-Rank Adaptation (QLoRA) in boosting performance. Notably, HOLD-Z secured the 9th place in the prestigious HOLD-Telugu DravidianLangTech@EACL-2024 shared task, showcasing its potential for tackling the complexities of hate and offensive comment classification.
UR - https://www.scopus.com/pages/publications/85189863475
UR - https://www.scopus.com/pages/publications/85189863475#tab=citedBy
M3 - Conference contribution
AN - SCOPUS:85189863475
T3 - DravidianLangTech 2024 - 4th Workshop on Speech, Vision, and Language Technologies for Dravidian Languages, Proceedings of the Workshop
SP - 134
EP - 139
BT - DravidianLangTech 2024 - 4th Workshop on Speech, Vision, and Language Technologies for Dravidian Languages, Proceedings of the Workshop
A2 - Chakravarthi, Bharathi Raja
A2 - Priyadharshini, Ruba
A2 - Madasamy, Anand Kumar
A2 - Thavareesan, Sajeetha
A2 - Sherly, Elizabeth
A2 - Nadarajan, Rajeswari
A2 - Ravikiran, Manikandan
PB - Association for Computational Linguistics (ACL)
Y2 - 22 March 2024
ER -