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Hate-Alert@DravidianLangTech-EACL2021: Ensembling strategies for Transformer-based Offensive language Detection

arXiv 2102.10084 ↗First posted 19 Feb 2021cs.CL cs.AIcited by 8

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Abstract (arXiv)

Social media often acts as breeding grounds for different forms of offensive content. For low resource languages like Tamil, the situation is more complex due to the poor performance of multilingual or language-specific models and lack of proper benchmark datasets. Based on this shared task, Offensive Language Identification in Dravidian Languages at EACL 2021, we present an exhaustive exploration of different transformer models, We also provide a genetic algorithm technique for ensembling different models. Our ensembled models trained separately for each language secured the first position in Tamil, the second position in Kannada, and the first position in Malayalam sub-tasks. The models and codes are provided.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 13 of its 41 references that are in the map. First posted on arXiv 19 Feb 2021.

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13 of 41 references.

References · 13

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1 more
  1. 2020Processing South Asian Languages Written in the Latin Script: the Dakshina Datasetcited by 35

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Citing papers per year: 2021: 4; 2022: 2; 2023: 1; 2024: 1.

8 papers.