2 papers
cs.CL2026
Which Medical Questions Deserve Rationales? Perturbation-Sensitive Selection for Robust QA
Yuexin Wu, Dayou Yu, Vasile Rus
Medical question-answering datasets often contain answer labels, whereas high-quality rationales remain scarce, noisy, or costly to validate. This changes the acquisition question:…
cs.MM2026
MPrune: Hierarchical Collaborative Pruning for Efficient Multi-Modal Multi-Agent Retrieval-Augmented Generation
Taolin Zhang, Weizi shao, Zijie Zhou +5
Recent advances in multi-modal retrieval-augmented generation (mRAG), which augments multi-modal large language models (MLLMs) with external knowledge, have shown that collective i…