Adapter-based fine-tuning of pre-trained multilingual language models for code-mixed and code-switched text classification

Himashi Rathnayake; Janani Sumanapala; Raveesha Rukshani; Surangika Ranathunga

doi:10.1007/s10115-022-01698-1

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Adapter-based fine-tuning of pre-trained multilingual language models for code-mixed and code-switched text classification

Himashi Rathnayake Janani Sumanapala Raveesha Rukshani Surangika Ranathunga

Year: 2022 Journal: Knowledge and Information Systems Vol: 64 (7)Pages: 1937-1966 Publisher: Springer Science+Business Media

DOI: 10.1007/s10115-022-01698-1

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Keywords:

Computer science Adapter (computing) Language identification Natural language processing Artificial intelligence Code (set theory) Language model Task (project management) Identification (biology) Code-switching Speech recognition Natural language Programming language Linguistics

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Hate Speech and Cyberbullying Detection

Physical Sciences → Computer Science → Artificial Intelligence

Natural Language Processing Techniques

Physical Sciences → Computer Science → Artificial Intelligence

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Physical Sciences → Computer Science → Artificial Intelligence

Adapter-based fine-tuning of pre-trained multilingual language models for code-mixed and code-switched text classification

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