Yichun Feng

AutoBioKG constructs context-aware biomedical knowledge graphs to improve scientific inference by encoding environmental conditions and entity attributes, outperforming baselines in multiple benchmarks.

The paper introduces a framework that combines large language models with knowledge graphs to improve factual accuracy in biomedical question answering, demonstrating effectiveness in drug repositioning and resistance prediction.