activity
20052026
most citedFairness-Aware Ranking in Search & Recommendation Systems with Application to LinkedIn Talent Search

352 citations · 1k across the 42 of their papers we have counts for

collaborators

52 papers

cs.AI2026

AegisVox: Factorized Privacy and Clinical Preservation for Long-Form Speech

Praphul Singh, Akshat Agarwal, Ratul Ghosh +5

Clinical speech reveals identity through both spoken identifiers and voice, yet its pauses, delivery, and speaker roles can also carry useful clinical evidence. Protecting that spe…

cs.CV2026

CheXmix: Unified Generative Pretraining for Vision Language Models in Medical Imaging

Ashwin Kumar, Robbie Holland, Corey Barrett +8

Recent medical multimodal foundation models are built as multimodal LLMs (MLLMs) by connecting a CLIP-pretrained vision encoder to an LLM using LLaVA-style finetuning. This two-sta…

cs.CL2026

From Attribution to Abstention: Training-Free Attention-Based Auditing for Clinical Summarization

Qianqi Yan, Huy Nguyen, Sumana Srivatsa +3

Deploying multimodal large language models (MLLMs) for clinical summarization demands not only fluent generation but also transparency about where each statement originates-and a m…

cs.AI2025

Balancing Safety and Helpfulness in Healthcare AI Assistants through Iterative Preference Alignment

Huy Nghiem, Swetasudha Panda, Devashish Khatwani +3

Large Language Models (LLMs) are increasingly used in healthcare, yet ensuring their safety and trustworthiness remains a barrier to deployment. Conversational medical assistants m…

cs.AI2025

OG-Rank: Learning to Rank Fast and Slow with Uncertainty and Reward-Trend Guided Adaptive Exploration

Praphul Singh, Corey Barrett, Sumana Srivasta +3

Clinicians need ranking systems that work in real time and still justify their choices. Motivated by the need for a low-latency, decoder-based reranker, we present OG-Rank, a singl…

cs.AI2025

JEDA: Query-Free Clinical Order Search from Ambient Dialogues

Praphul Singh, Corey Barrett, Sumana Srivasta +4

Clinical conversations mix explicit directives (order a chest X-ray) with implicit reasoning (the cough worsened overnight, we should check for pneumonia). Many systems rely on LLM…