4 papers
How to make Medical AI Systems safer? Simulating Vulnerabilities, and Threats in Multimodal Medical RAG System
Kaiwen Zuo, Zelin Liu, Raman Dutt +4
Large Vision-Language Models (LVLMs) augmented with Retrieval-Augmented Generation (RAG) are increasingly employed in medical AI to enhance factual grounding through external clini…
GLANCE: Graph Logic Attention Network with Cluster Enhancement for Heterophilous Graph Representation Learning
Zhongtian Sun, Anoushka Harit, Alexandra Cristea +2
Graph Neural Networks (GNNs) have demonstrated significant success in learning from graph-structured data but often struggle on heterophilous graphs, where connected nodes differ i…
Actionable Interpretability via Causal Hypergraphs: Unravelling Batch Size Effects in Deep Learning
Zhongtian Sun, Anoushka Harit, Pietro Lio
While the impact of batch size on generalisation is well studied in vision tasks, its causal mechanisms remain underexplored in graph and text domains. We introduce a hypergraph-ba…
KG4Diagnosis: A Hierarchical Multi-Agent LLM Framework with Knowledge Graph Enhancement for Medical Diagnosis
Kaiwen Zuo, Yirui Jiang, Fan Mo +1
Integrating Large Language Models (LLMs) in healthcare diagnosis demands systematic frameworks that can handle complex medical scenarios while maintaining specialized expertise. We…