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cs.AI2026
Hierarchical MoE for Multi-Modal ILD Diagnosis
Alec K. Peltekian, Gorkem Durak, Halil Ertugrul Aktas +9
Mixture-of-experts (MoE) models combine specialized predictors under learned routing, offering a principled mechanism for leveraging heterogeneity in medical data. We present a hie…
cs.AI2026
A decodability criterion predicts when hidden-state selection beats majority voting in large language models
Zhixiang wang, Ziliang Hong, Ulas Bagci
Combining the answers a large language model (LLM) samples for a question into one decision is a test-time information fusion problem, usually solved by majority voting. Voting is…