5 papers
Training-Free Representation Guidance for Diffusion Models with a Representation Alignment Projector
Wenqiang Zu, Shenghao Xie, Bo Lei +1
Recent progress in generative modeling has enabled high-quality visual synthesis with diffusion-based frameworks, supporting controllable sampling and large-scale training. Inferen…
M4GN: Mesh-based Multi-segment Hierarchical Graph Network for Dynamic Simulations
Bo Lei, Victor M. Castillo, Yeping Hu
Mesh-based graph neural networks (GNNs) have become effective surrogates for PDE simulations, yet their deep message passing incurs high cost and over-smoothing on large, long-rang…
HDGlyph: A Hierarchical Disentangled Glyph-Based Framework for Long-Tail Text Rendering in Diffusion Models
Shuhan Zhuang, Mengqi Huang, Fengyi Fu +3
Visual text rendering, which aims to accurately integrate specified textual content within generated images, is critical for various applications such as commercial design. Despite…
Exploring Representation Invariance in Finetuning
Wenqiang Zu, Shenghao Xie, Hao Chen +9
Foundation models pretrained on large-scale natural images are widely adapted to various cross-domain low-resource downstream tasks, benefiting from generalizable and transferable…
Multi-Modal Latent Variables for Cross-Individual Primary Visual Cortex Modeling and Analysis
Yu Zhu, Bo Lei, Chunfeng Song +3
Elucidating the functional mechanisms of the primary visual cortex (V1) remains a fundamental challenge in systems neuroscience. Current computational models face two critical limi…