3 papers
cs.CL2026
ABBA-Adapters: Efficient and Expressive Fine-Tuning of Foundation Models
Raghav Singhal, Kaustubh Ponkshe, Rohit Vartak +1
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 F…
cs.LG2025
Fed-SB: A Silver Bullet for Extreme Communication Efficiency and Performance in (Private) Federated LoRA Fine-Tuning
Raghav Singhal, Kaustubh Ponkshe, Rohit Vartak +2
Low-Rank Adaptation (LoRA) has become ubiquitous for efficiently fine-tuning foundation models. However, federated fine-tuning using LoRA is challenging due to suboptimal updates a…
cs.CL2025
"What's Up, Doc?": Analyzing How Users Seek Health Information in Large-Scale Conversational AI Datasets
Akshay Paruchuri, Maryam Aziz, Rohit Vartak +5
People are increasingly seeking healthcare information from large language models (LLMs) via interactive chatbots, yet the nature and inherent risks of these conversations remain l…