2 papers
cs.LG2026
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…
cs.CV2026
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 \…