1 citations · 3 across the 6 of their papers we have counts for
7 papers
Self-Conditioning Enables Deep Sequential Reasoning in Flow Matching
Zeyang Zhang, Linxiang Gao, Meiqi Gu +4
Recent work has explored visual reasoning through image generation, where models solve visual-reasoning problems by directly generating solution images. Intuitively, iterative samp…
From Trajectories to Phenotypes: Disease Progression as Structural Priors for Multi-organ Imaging Representation Learning
Zian Wang, Lizhen Lan, Guangming Wang +9
Imaging-derived phenotypes (IDPs) summarize multi-organ physiology but provide only static snapshots of diseases that evolve over time. In contrast, longitudinal electronic health…
Differences in Text Generated by Diffusion and Autoregressive Language Models
Zeyang Zhang, Chengwei Liang, Xingyan Chen +4
Diffusion language models (DLMs) are promising alternatives to autoregressive language models (ARMs), yet the intrinsic differences in their generated text remain underexplored. We…
Enabling Ultra-Fast Cardiovascular Imaging Across Heterogeneous Clinical Environments with A Generalist Foundation Model and Multimodal Database
Zi Wang, Mingkai Huang, Zhang Shi +61
Multimodal cardiovascular magnetic resonance (CMR) imaging provides comprehensive and non-invasive insights into cardiovascular disease (CVD) diagnosis and underlying mechanisms. D…
Towards Black-Box Membership Inference Attack for Diffusion Models
Jingwei Li, Jing Dong, Tianxing He +1
Given the rising popularity of AI-generated art and the associated copyright concerns, identifying whether an artwork was used to train a diffusion model is an important research t…
Learning Time-Invariant Representations for Individual Neurons from Population Dynamics
Lu Mi, Trung Le, Tianxing He +2
Neurons can display highly variable dynamics. While such variability presumably supports the wide range of behaviors generated by the organism, their gene expressions are relativel…
LatticeGen: A Cooperative Framework which Hides Generated Text in a Lattice for Privacy-Aware Generation on Cloud
Mengke Zhang, Tianxing He, Tianle Wang +5
In the current user-server interaction paradigm of prompted generation with large language models (LLM) on cloud, the server fully controls the generation process, which leaves zer…