5 papers
Spike-driven Large Language Model
Han Xu, Xuerui Qiu, Baiyu Chen +7
Current Large Language Models (LLMs) are primarily based on large-scale dense matrix multiplications. Inspired by the brain's information processing mechanism, we explore the funda…
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…
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…
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…