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- W4385573910 abstract "Performance of downstream NLP tasks on code-switched Hindi-English (aka ) continues to remain a significant challenge. Intuitively, Hindi and English corpora should aid improve task performance on Hinglish. We show that meta-learning framework can effectively utilize the the labelled resources of the downstream tasks in the constituent languages. The proposed approach improves the performance on downstream tasks on code-switched language. We experiment with code-switching benchmark GLUECoS and report significant improvements." @default.
- W4385573910 created "2023-08-05" @default.
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- W4385573910 date "2022-01-01" @default.
- W4385573910 modified "2023-09-24" @default.
- W4385573910 title "On Utilizing Constituent Language Resources to Improve Downstream Tasks in Hinglish" @default.
- W4385573910 doi "https://doi.org/10.18653/v1/2022.findings-emnlp.283" @default.
- W4385573910 hasPublicationYear "2022" @default.
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