Author

Yao-Jun Hu

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Preprint Aug 2026

SeVeR: Selective Visual Exposure and Retrieval for 3D Medical Image Question Answering

SeVeR is proposed, a selective visual exposure framework that compresses dense volumes into modality-wise prototypes and retrieves complementary multi-level evidence with change-aware gated attention during decoding, trained with a marginal-utility self-consistency objective that suppresses unhelpful retrieval.

Yao-Jun Hu, Danyang Tu, Yang Liu et al. · 0 citations

Jul 2026

D3O: Dynamic Distribution Distillation for Ordinal Regression

The proposed D3O, a dynamic distribution distillation framework that replaces static supervision with training-driven evolution of ordinal label distributions via self-distillation, introduces a contrastive ordinal-aware label enhancement module that leverages vision-language alignment to recover refined label distributions capturing both inter-class ambiguity and instance-level uncertainty.

Chunlai Dong, Yao-Jun Hu, Yuyang Xu et al. · arXiv.org · 0 citations