7 papers
Computational and Statistical Guarantees of the \textit{c}-Rectified flow
Leda Wang, Zhehao Xu, Qiang Liu +1
Recently, rectified flow has emerged as a fundamental framework for large-scale image generation, powering state-of-the-art systems such as FLUX.1 and Stable Diffusion 3. Despite i…
Signed Rectified Flow: Negativity-Controlled Generation
Runlong Liao, Baiyu Su, Lizhang Chen +1
We introduce Signed Rectified Flow (Signed RF), a generalization of Rectified Flow that targets the signed measure , where , is the di…
Momentum Guidance: Plug-and-Play Guidance for Flow Models
Runlong Liao, Jian Yu, Baiyu Su +3
Flow-based generative methods offer a simple and effective framework for high-fidelity generation, yet pretrained flow models are rarely used in their vanilla conditional form: in…
-Balancing for Mixture-of-Experts Training
Lizhang Chen, Jonathan Li, Qi Wang +5
Mixture-of-Experts (MoE) models rely on balanced expert utilization to fully realize their scalability. However, existing load-balancing methods are largely heuristic and operate o…
Tadpole: Autoencoders as Foundation Models for 3D PDEs with Online Learning
Qiang Liu, Felix Koehler, Benjamin Holzschuh +1
We introduce Tadpole, a novel foundation model for three-dimensional partial differential equations (PDEs) that addresses key challenges in transferability, scalability to high dim…
Reading the Cell, Designing the Cure: Perturbation-Conditioned Molecular Diffusion for Function-Oriented Drug Design
Ziyu Xu, Zijian Zhang, Liang Wang +3
When reliable target structures are unavailable at scale or phenotypes arise from dysregulated pathways, transcriptomic perturbations provide a system-level functional readout for…