activity
20062026
most citedThe Multimodal Driver Monitoring Database: A Naturalistic Corpus to Study Driver Attention

44 citations · 88 across the 26 of their papers we have counts for

collaborators

27 papers

cs.CR2026

Privacy Foundations for Multi-Institutional Scientific Artificial Intelligence

Olivera Kotevska, Sumit Jha, Aurélien Bellet +5

Scientific artificial intelligence (AI), spanning foundation models (FMs) to federated data-analysis pipelines, is becoming shared infrastructure across national laboratories, univ…

cs.AI2026

Consilience: Conformally Calibrated Communication Control for Hidden-Profile Multi-Agent Reasoning

Abhijith Babu, Ramneet Kaur, Vishal Pramanik +7

Multi-agent LLM systems can improve reasoning by pooling diverse perspectives, but their effectiveness depends on coordinating communication, particularly in hidden-profile setting…

cs.AI2026

Beyond the Transcript: Detecting Covert Co ordination in Latent Multi-Agent Communication

Ramneet Kaur, Pradyumna Chari, Ramesh Raskar +3

Language-model agents can communicate through continuous hidden states that are invisible in public transcripts, creating opportunities for covert harmful coordination. We introduc…

cs.DC2026

Discovering KV Cache Eviction Policies via LLM-Guided Program Evolution

Pratik Poudel, Yanzhao Wu, Sumit Jha +1

KV cache compression is critical for long-context inference, yet effective eviction policies remain difficult to design: existing prefill-stage methods often rely on hand-crafted s…

cs.AI2026

HiComm: Hierarchical Communication for Multi-agent Reinforcement Learning

Runze Zhao, Dongruo Zhou, Sumit Kumar Jha +2

Cooperative multi-agent reinforcement learning (MARL) often relies on communication to mitigate partial observability, yet most existing protocols treat messages as flat dense vect…

cs.AI2026

Closed-Loop Neural Activation Control in Vision-Language-Action Models

Abhijith Babu, Ramneet Kaur, Nathaniel D. Bastian +5

Vision-Language-Action (VLA) models can be steered at test time by intervening on semantically meaningful internal directions, but existing methods use a fixed steering coefficient…