From the 1 of 7 linked papers with an AI index.
7 papers
Learning in Curved Weight Space:Exponential-Linear Weight Reparameterization for Improved Optimization
Ethan Smith
The paper proposes a new weight reparameterization that combines an exponential and a linear pathway, creating a curved parameter space that enables more proportional updates and s…
DiffusionBench: On Holistic Evaluation of Diffusion Transformers
Xingjian Leng, Jaskirat Singh, Zhanhao Liang +5
Diffusion transformer (DiT) research on image generation has converged to a single evaluation setup: class-conditional generation on ImageNet. While methods improve the FID and rel…
MRT: Masked Region Transformer for Layered Image Generation and Editing at Scale
Zhicong Tang, Zhao Zhang, Jingye Chen +6
Layered image generation and editing is a fundamental capability that enables layer-wise reuse, editing, and composition of generated visual content, analogous to word-level editin…
NOBLE: Accelerating Transformers with Nonlinear Low-Rank Branches
Ethan Smith
We introduce NOBLE (Nonlinear lOw-rank Branch for Linear Enhancement), an architectural augmentation that adds nonlinear low-rank branches to transformer linear layers. Unlike LoRA…
From Tokens to Numbers: Continuous Number Modeling for SVG Generation
Michael Ogezi, Martin Bell, Freda Shi +1
For certain image generation tasks, vector graphics such as Scalable Vector Graphics (SVGs) offer clear benefits such as increased flexibility, size efficiency, and editing ease, b…
EZIGen: Enhancing zero-shot personalized image generation with precise subject encoding and decoupled guidance
Zicheng Duan, Yuxuan Ding, Chenhui Gou +3
Zero-shot personalized image generation models aim to produce images that align with both a given text prompt and subject image, requiring the model to incorporate both sources of…