8 papers
MedicalHarness: A Controlled Evaluation of LLMs and Agent Harnesses on Medical Tasks
Ziqing Wang, Lili Zhao, Kaize Ding
LLM agents are increasingly built for medical work and scored on clinical benchmarks. Each such score, however, comes from a model running inside an agent harness, the system that…
Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology
Tianyu Liu, Ziqing Wang, Zhaokang Liang +12
Predicting immune biomarkers associated with the tumor immune microenvironment (TIME) is critical for advancing precision oncology, yet existing approaches are largely limited to s…
Can Post-Training Turn LLMs into Good Medical Coders? An Empirical Study of Generative ICD Coding
Ziqing Wang, Weihao Li, Shijie Chen +2
Automated International Classification of Diseases (ICD) coding is a core medical-coding task for billing, epidemiology, and clinical decision support. Generative large language mo…
Benchmarking AI Agents for Addressing Scientific Challenges Across Scales
Tianyu Liu, Allen Xin Wang, Antonia Panescu +30
AI agents are increasingly being developed to accelerate scientific discovery, yet their practical capabilities in real research settings remain poorly understood. Existing benchma…
LatentDx: Latent Multi-Agent Communication for Cross-Hospital Rare-Disease Diagnosis
Ziqing Wang, Lili Zhao, Kaize Ding
Rare diseases affect over million patients across more than conditions, yet no single hospital encounters enough cases of any one condition for reliable diagnosis.…
MedLoCoMo: A Long-Context Multi-Session Medical Dialogue Benchmark for Large Language Models
Zeyu Zhang, Ziqing Wang, Kaize Ding
MedLoCoMo is a Medical Long-Context Memory benchmark for patient-specific clinical reasoning over multi-admission medical dialogue. Existing medical QA benchmarks largely test shor…
MolMem: Memory-Augmented Agentic Reinforcement Learning for Sample-Efficient Molecular Optimization
Ziqing Wang, Yibo Wen, Abhishek Pandy +2
In drug discovery, molecular optimization aims to iteratively refine a lead compound to improve molecular properties while preserving structural similarity to the original molecule…
AMANDA: Agentic Medical Knowledge Augmentation for Data-Efficient Medical Visual Question Answering
Ziqing Wang, Chengsheng Mao, Xiaole Wen +2
Medical Multimodal Large Language Models (Med-MLLMs) have shown great promise in medical visual question answering (Med-VQA). However, when deployed in low-resource settings where…