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Rohit Vartak

2 accepted papers

2026

ABBA-Adapters: Efficient and Expressive Fine-Tuning of Foundation Models

ICLR 2026poster

Large Language Models have demonstrated strong performance across a wide range of tasks, but adapting them efficiently to new domains remains a key challenge. Parameter-Efficient Fine-Tuning (PEFT) methods address this by introducing lightweight, trainable modules while keeping most pre-trained weig…

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2025

“What’s Up, Doc?”: Analyzing How Users Seek Health Information in Large-Scale Conversational AI Datasets

EMNLP 2025

People are increasingly seeking healthcare information from large language models (LLMs) via interactive chatbots, yet the nature and inherent risks of these conversations remain largely unexplored. In this paper, we filter large-scale conversational AI datasets to achieve HealthChat-11K, a curated