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indicnlp@kgp at DravidianLangTech-EACL2021: Offensive Language Identification in Dravidian Languages

arXiv 2102.07150 ↗First posted 14 Feb 2021cs.CLcited by 4

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Abstract (arXiv)

The paper presents the submission of the team indicnlp@kgp to the EACL 2021 shared task "Offensive Language Identification in Dravidian Languages." The task aimed to classify different offensive content types in 3 code-mixed Dravidian language datasets. The work leverages existing state of the art approaches in text classification by incorporating additional data and transfer learning on pre-trained models. Our final submission is an ensemble of an AWD-LSTM based model along with 2 different transformer model architectures based on BERT and RoBERTa. We achieved weighted-average F1 scores of 0.97, 0.77, and 0.72 in the Malayalam-English, Tamil-English, and Kannada-English datasets ranking 1st, 2nd, and 3rd on the respective tasks.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 16 of its 21 references that are in the map. First posted on arXiv 14 Feb 2021.

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16 of 21 references.

References · 16

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4 more
  1. 2018On the Limitations of Unsupervised Bilingual Dictionary Inductioncited by 61
  2. 2020A Sentiment Analysis Dataset for Code-Mixed Malayalam-Englishcited by 50
  3. 2016How Transferable are Neural Networks in NLP Applications?cited by 23
  4. 2020Gauravarora@HASOC-Dravidian-CodeMix-FIRE2020: Pre-training ULMFiT on Synthetically Generated Code-Mixed Data for Hate Speech Detectioncited by 5

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Citing papers per year: 2021: 3; 2022: 0; 2023: 0; 2024: 0; 2025: 1.

4 papers.