@inproceedings{kumari-etal-2023-ml-ai,
title = "{ML}{\&}{AI}{\_}{IIITR}anchi@{D}ravidian{L}ang{T}ech:Leveraging Transfer Learning for the discernment of Fake News within the Linguistic Domain of {D}ravidian Language",
author = "Kumari, Kirti and
Jha, Shirish Shekhar and
Dayanand, Zarikunte Kunal and
Sharma, Praneesh",
editor = "Chakravarthi, Bharathi R. and
Priyadharshini, Ruba and
M, Anand Kumar and
Thavareesan, Sajeetha and
Sherly, Elizabeth",
booktitle = "Proceedings of the Third Workshop on Speech and Language Technologies for Dravidian Languages",
month = sep,
year = "2023",
address = "Varna, Bulgaria",
publisher = "INCOMA Ltd., Shoumen, Bulgaria",
url = "https://aclanthology.org/2023.dravidianlangtech-1.28",
pages = "198--206",
abstract = "The primary focus of this research endeavor lies in detecting and mitigating misinformation within the intricate framework of the Dravidian language. A notable feat was achieved by employing fine-tuning methodologies on the highly acclaimed Indic BERT model, securing a commendable fourth rank in a prestigious competition organized by DravidianLangTech 2023 while attaining a noteworthy macro F1-Score of 0.78. To facilitate this undertaking, a diverse and comprehensive dataset was meticulously gathered from prominent social media platforms, including but not limited to Facebook and Twitter. The overarching objective of this collaborative initiative was to proficiently discern and categorize news articles into either the realm of veracity or deceit through the astute application of advanced machine learning techniques, coupled with the astute exploitation of the distinctive linguistic idiosyncrasies inherent to the Dravidian language.",
}
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%0 Conference Proceedings
%T ML&AI_IIITRanchi@DravidianLangTech:Leveraging Transfer Learning for the discernment of Fake News within the Linguistic Domain of Dravidian Language
%A Kumari, Kirti
%A Jha, Shirish Shekhar
%A Dayanand, Zarikunte Kunal
%A Sharma, Praneesh
%Y Chakravarthi, Bharathi R.
%Y Priyadharshini, Ruba
%Y M, Anand Kumar
%Y Thavareesan, Sajeetha
%Y Sherly, Elizabeth
%S Proceedings of the Third Workshop on Speech and Language Technologies for Dravidian Languages
%D 2023
%8 September
%I INCOMA Ltd., Shoumen, Bulgaria
%C Varna, Bulgaria
%F kumari-etal-2023-ml-ai
%X The primary focus of this research endeavor lies in detecting and mitigating misinformation within the intricate framework of the Dravidian language. A notable feat was achieved by employing fine-tuning methodologies on the highly acclaimed Indic BERT model, securing a commendable fourth rank in a prestigious competition organized by DravidianLangTech 2023 while attaining a noteworthy macro F1-Score of 0.78. To facilitate this undertaking, a diverse and comprehensive dataset was meticulously gathered from prominent social media platforms, including but not limited to Facebook and Twitter. The overarching objective of this collaborative initiative was to proficiently discern and categorize news articles into either the realm of veracity or deceit through the astute application of advanced machine learning techniques, coupled with the astute exploitation of the distinctive linguistic idiosyncrasies inherent to the Dravidian language.
%U https://aclanthology.org/2023.dravidianlangtech-1.28
%P 198-206
Markdown (Informal)
[ML&AI_IIITRanchi@DravidianLangTech:Leveraging Transfer Learning for the discernment of Fake News within the Linguistic Domain of Dravidian Language](https://aclanthology.org/2023.dravidianlangtech-1.28) (Kumari et al., DravidianLangTech-WS 2023)
ACL