1k citations · 1.1k across the 4 of their papers we have counts for
4 papers
LoRA-Muon: Spectral Steepest Descent on the Low-Rank Manifold
Franz Louis Cesista, Katherine Crowson, Cédric Simal +1
Low-Rank Adaptation (LoRA) significantly reduces compute and memory costs for finetuning Deep Learning models but is often harder to tune than dense training: when using factor-wis…
Scalable High-Resolution Pixel-Space Image Synthesis with Hourglass Diffusion Transformers
Katherine Crowson, Stefan Andreas Baumann, Alex Birch +3
We present the Hourglass Diffusion Transformer (HDiT), an image generative model that exhibits linear scaling with pixel count, supporting training at high-resolution (e.g. $1024 \…
LAION-5B: An open large-scale dataset for training next generation image-text models
Christoph Schuhmann, Romain Beaumont, Richard Vencu +13
Groundbreaking language-vision architectures like CLIP and DALL-E proved the utility of training on large amounts of noisy image-text data, without relying on expensive accurate la…
VQGAN-CLIP: Open Domain Image Generation and Editing with Natural Language Guidance
Katherine Crowson, Stella Biderman, Daniel Kornis +4
Generating and editing images from open domain text prompts is a challenging task that heretofore has required expensive and specially trained models. We demonstrate a novel method…