1 citations · 3 across the 20 of their papers we have counts for
20 papers
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…
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…
Thinking in Uncertainty: Mitigating Hallucinations in MLRMs with Latent Entropy-Aware Decoding
Zhongxing Xu, Zhonghua Wang, Zhe Qian +10
Recent advancements in multimodal large reasoning models (MLRMs) have significantly improved performance in visual question answering. However, we observe that transition words (e.…
OneVision-Encoder: Codec-Aligned Sparsity as a Foundational Principle for Multimodal Intelligence
Feilong Tang, Xiang An, Yunyao Yan +16
Hypothesis. Artificial general intelligence is, at its core, a compression problem. Effective compression demands resonance: deep learning scales best when its architecture aligns…
A General Model for Retinal Segmentation and Quantification
Zhonghua Wang, Lie Ju, Sijia Li +12
Retinal imaging is fast, non-invasive, and widely available, offering quantifiable structural and vascular signals for ophthalmic and systemic health assessment. This accessibility…
PsychEthicsBench: Evaluating Large Language Models Against Australian Mental Health Ethics
Yaling Shen, Stephanie Fong, Yiwen Jiang +9
The increasing integration of large language models (LLMs) into mental health applications necessitates robust frameworks for evaluating professional safety alignment. Current eval…