4 papers
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…
LoRA Diffusion: Zero-Shot LoRA Synthesis for Diffusion Model Personalization
Ethan Smith, Rami Seid, Alberto Hojel +2
Low-Rank Adaptation (LoRA) and other parameter-efficient fine-tuning (PEFT) methods provide low-memory, storage-efficient solutions for personalizing text-to-image models. However,…
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…