Papers by Suraj Tripathi

1 papers
PRO-CS : An Instance-Based Prompt Composition Technique for Code-Switched Tasks (2022.emnlp-main)

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Challenge: Code-switching (CS) data is ubiquitous in today’s globalized world, but the dearth of annotated datasets in code-switch tasks poses a significant challenge for transfer learning in limited-resource setups.
Approach: They propose a prompt composition technique that outperforms prompt-tuning and fine-tuned prompt-based prompt composition techniques for CS tasks that combine language and task knowledge.
Outcome: The proposed approach outperforms prompt-tuning and fine-tuned approaches on 10 datasets across 4 languages and achieves competitive results in low-resource cross-lingual and cross-task setting.

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