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cs.CV2026
ReMoE: Report-Guided Mixture-of-Experts for Multimodal OCT/OCTA Anomaly Detection
Zihan Nie, Qincheng Qiao, Muhao Xu +4
Multimodal medical anomaly detection identifies samples deviating from normal patterns, where scarce abnormal cases make normality modeling from normal data practical. In retinal O…
cs.CV2026
CFR-Net:Collaborative Feature Refinement Network for Medical Image Anomaly Detection
Zihan Nie, Muhao Xu, Wei Feng +8
Medical image anomaly detection is central to timely diagnosis and clinical decision support, yet abnormal samples are costly to collect because of disease rarity, privacy concerns…
cs.CL2026
MMKU-Bench: A Multimodal Update Benchmark for Diverse Visual Knowledge
Baochen Fu, Yuntao Du, Cheng Chang +6
As real-world knowledge continues to evolve, the parametric knowledge acquired by multimodal models during pretraining becomes increasingly difficult to remain consistent with real…