MED-VRAG reaches 78.6% average accuracy on four medical QA benchmarks by iteratively retrieving PMC page images with ColQwen2.5 embeddings and a VLM that refines queries over up to three rounds.
Prompts and Output Schema Stage-2 filter prompt(Qwen3-30B-A3B, sharded MapReduce;target k=25 in map shards, 100 in reduce): You are a medical document retrieval expert
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Iterative Multimodal Retrieval-Augmented Generation for Medical Question Answering
MED-VRAG reaches 78.6% average accuracy on four medical QA benchmarks by iteratively retrieving PMC page images with ColQwen2.5 embeddings and a VLM that refines queries over up to three rounds.