Biomedical QA

Biomedical question answering studies how to answer questions about medicine, clinical care, and biological research accurately and with support from relevant evidence. Systems commonly combine large language models with retrieval-augmented generation, biomedical knowledge graphs, and multi-step reasoning or agent workflows. Benchmarks such as PubMedQA, MedQA, and BioASQ test tasks ranging from factual recall to multi-hop reasoning across documents, while newer evaluations examine citations, uncertainty, and patient-specific context. A central challenge is making retrieved evidence reliably improve answers: results vary by model and task, and conflicting or incomplete sources make calibration and appropriate abstention important.