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Hallucination-Aware Diffusion Sampling for Inverse Problems via Robust Prior Updates
Pengfei Jin, Yiqi Tian, Kailong Fan +2
Diffusion-based inverse problem solvers can produce realistic reconstructions, but realism alone does not ensure that the recovered details are supported by the measurement. We stu…
LiFT: Lifted Inter-slice Feature Trajectories for 3D Image Generation from 2D Generators
Xinhe Zhang, Yuyang Zhang, Pengfei Jin +3
High-resolution 3D medical image generation remains challenging because fully volumetric models are computationally expensive, while efficient 2D slice generators often fail to pre…
DuetMoE: Coupling Inter- and Intra-Subgroup Robustness for Fair Medical Image Analysis
Yiqi Tian, Sangjoon Park, Jinwoong Park +4
As medical AI expands across diverse healthcare settings worldwide, equitable performance across patient populations is becoming essential to trustworthy clinical use. Fairness in…
Local Intrinsic Dimension Unveils Hallucinations in Diffusion Models
Bartlomiej Sobieski, Matthew Tivnan, Dawid Płudowski +4
Diffusion models are prone to generating structural hallucinations - samples that match the statistical properties of the training data yet defy underlying structural rules, result…