collaborators

5 papers

cs.CV2026

GigaPath-Flash and GigaTIME-Flash: Efficient Pathology Foundation Models for Whole-Slide and Tumor Microenvironment Analysis

Naoto Usuyama, Jeya Maria Jose Valanarasu, Sicong Yao +27

Foundation models have emerged as a driving force in computational pathology, with the potential to transform cancer diagnosis, prognosis, and treatment selection by learning trans…

cs.AI2026

HealthAgentBench: A Unified Benchmark Suite of Realistic Agentic Healthcare Environments for Challenging Frontier AI Agents

Qianchu Liu, Sheng Zhang, Guanghui Qin +16

As AI agents become increasingly capable of complex, long-horizon reasoning, rigorous and holistic evaluation is essential for measuring progress toward real-world healthcare appli…

cs.CV2026

Scaling medical imaging report generation with multimodal reinforcement learning

Qianchu Liu, Sheng Zhang, Guanghui Qin +11

Frontier models have demonstrated remarkable capabilities in understanding and reasoning with natural-language text, but they still exhibit major competency gaps in multimodal unde…

cs.AI2025

OctoMed: Data Recipes for State-of-the-Art Multimodal Medical Reasoning

Timothy Ossowski, Sheng Zhang, Qianchu Liu +5

High-quality and carefully curated data is a cornerstone of training medical large language models, as it directly impacts both generalization and robustness to unseen clinical tas…

cs.CL2025

Be My Eyes: Extending Large Language Models to New Modalities Through Multi-Agent Collaboration

James Y. Huang, Sheng Zhang, Qianchu Liu +5

Large Language Models (LLMs) have demonstrated remarkable capabilities in challenging, knowledge-intensive reasoning tasks. However, extending LLMs to perceive and reason over a ne…