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        <title>On Utilizing Constituent Language Resources to Improve Downstream Tasks in Hinglish</title>
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    <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.</abstract>
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%0 Conference Proceedings
%T On Utilizing Constituent Language Resources to Improve Downstream Tasks in Hinglish
%A Kumar, Vishwajeet
%A Murthy, Rudra
%A Dhamecha, Tejas
%Y Goldberg, Yoav
%Y Kozareva, Zornitsa
%Y Zhang, Yue
%S Findings of the Association for Computational Linguistics: EMNLP 2022
%D 2022
%8 December
%I Association for Computational Linguistics
%C Abu Dhabi, United Arab Emirates
%F kumar-etal-2022-utilizing
%X 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.
%R 10.18653/v1/2022.findings-emnlp.283
%U https://aclanthology.org/2022.findings-emnlp.283/
%U https://doi.org/10.18653/v1/2022.findings-emnlp.283
%P 3859-3865

Markdown (Informal)

[On Utilizing Constituent Language Resources to Improve Downstream Tasks in Hinglish](https://aclanthology.org/2022.findings-emnlp.283/) (Kumar et al., Findings 2022)

• On Utilizing Constituent Language Resources to Improve Downstream Tasks in Hinglish (Kumar et al., Findings 2022)

ACL

• Vishwajeet Kumar, Rudra Murthy, and Tejas Dhamecha. 2022. On Utilizing Constituent Language Resources to Improve Downstream Tasks in Hinglish. In Findings of the Association for Computational Linguistics: EMNLP 2022, pages 3859–3865, Abu Dhabi, United Arab Emirates. Association for Computational Linguistics.