Papers by Nalin Kumar

2 papers
LEEETs-Dial: Linguistic Entrainment in End-to-End Task-oriented Dialogue systems (2024.findings-naacl)

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Challenge: Linguistic entrainment is a phenomenon where linguistic patterns employed by conversational participants converge to one another.
Approach: They propose methods for achieving dialogue entrainment in a task-oriented dialogue system using shared vocabulary.
Outcome: The proposed model produces significantly better entrainment than the base model.
Modular Monolingual Adaptation using Pretrained Language Models (2026.acl-industry)

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Challenge: Existing approaches to building monolingual models for low-resource languages require a full model tuning process.
Approach: They propose a modular approach to build monolingual models for low-resource languages by finetuning the whole model on the target language.
Outcome: The proposed model improves on natural language understanding tasks on Scottish Gaelic, Irish, and Quechua with Quechuan being a very low-resource language.

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