collaborators

5 papers

cs.LG2026

CPAgents: Agentic Composite Phenotype Generation for Cardiac Disease Association

Zuoou Li, Wenlong Zhao, Kelly Yu +5

Identifying robust associations between cardiac imaging phenotypes and clinical diseases is fundamental to population-scale cardiovascular research and reliable risk stratification…

cs.CV2026

Wasserstein Equilibrium Decoding for Reliable Medical Visual Question Answering

Luca Hagen, Johanna P. Müller, Weitong Zhang +2

Small vision-language models (2-8B) are well-suited for clinical deployment due to privacy constraints, limited connectivity, and low-latency requirements favouring on-device or on…

cs.AI2026

AutoResearchClaw: Self-Reinforcing Autonomous Research with Human-AI Collaboration

Jiaqi Liu, Shi Qiu, Mairui Li +33

Automating scientific discovery requires more than generating papers from ideas. Real research is iterative: hypotheses are challenged from multiple perspectives, experiments fail…

cs.AI2025

Multi-Agent Reasoning for Cardiovascular Imaging Phenotype Analysis

Weitong Zhang, Mengyun Qiao, Chengqi Zang +4

Identifying associations between imaging phenotypes, disease risk factors, and clinical outcomes is essential for understanding disease mechanisms. However, traditional approaches…

cs.CV2025

Towards Effective MLLM Jailbreaking Through Balanced On-Topicness and OOD-Intensity

Zuoou Li, Weitong Zhang, Jingyuan Wang +4

Multimodal large language models (MLLMs) are widely used in vision-language reasoning tasks. However, their vulnerability to adversarial prompts remains a serious concern, as safet…