activity
20242026
most citedMedVLM-R1: Incentivizing Medical Reasoning Capability of Vision-Language Models (VLMs) via Reinforcement Learning

1 citations · 1 across the 3 of their papers we have counts for

collaborators

7 papers

cs.RO2026

Behavior Cloning for Active Perception with Low-Resolution Egocentric Vision

Anthony Bilic, Chen Chen, Ladislau Bölöni

We investigate whether behavior cloning is sufficient to produce active perception in a structured object-finding task. A low-cost robot arm equipped with a wrist-mounted egocentri…

cs.AI2026

RealICU: Do LLM Agents Understand Long-Context ICU Data? A Benchmark Beyond Behavior Imitation

Chengzhi Shen, Weixiang Shen, Tobias Susetzky +7

Intensive care units (ICU) generate long, dense and evolving streams of clinical information, where physicians must repeatedly reassess patient states under time pressure, undersco…

eess.IV2025

Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction

Niklas Bubeck, Suprosanna Shit, Chen Chen +8

Cardiac Magnetic Resonance (CMR) imaging is a critical tool for diagnosing and managing cardiovascular disease, yet its utility is often limited by the sparse acquisition of 2D sho…

cs.LG2025

Addressing Benchmarking Gaps in Large Language Models for Health and Medicine with Dynamic Red-Teaming

Jiazhen Pan, Bailiang Jian, Paul Hager +19

Large language models (LLMs) are increasingly used to answer health-related questions and support healthcare workflows, yet evidence for their safety still relies heavily on static…

eess.IV2025

Towards Cardiac MRI Foundation Models: Comprehensive Visual-Tabular Representations for Whole-Heart Assessment and Beyond

Yundi Zhang, Paul Hager, Che Liu +4

Cardiac magnetic resonance imaging is the gold standard for non-invasive cardiac assessment, offering rich spatio-temporal views of the cardiac anatomy and physiology. Patient-leve…

cs.CV20251 cited

MedVLM-R1: Incentivizing Medical Reasoning Capability of Vision-Language Models (VLMs) via Reinforcement Learning

Jiazhen Pan, Che Liu, Junde Wu +6

Reasoning is a critical frontier for advancing medical image analysis, where transparency and trustworthiness play a central role in both clinician trust and regulatory approval. A…