3 papers
cs.LG2025
HVAdam: A Full-Dimension Adaptive Optimizer
Yiheng Zhang, Shaowu Wu, Yuanzhuo Xu +4
Adaptive optimizers such as Adam have achieved great success in training large-scale models like large language models and diffusion models. However, they often generalize worse th…
cs.CV2025
Flow to the Mode: Mode-Seeking Diffusion Autoencoders for State-of-the-Art Image Tokenization
Kyle Sargent, Kyle Hsu, Justin Johnson +2
Since the advent of popular visual generation frameworks like VQGAN and latent diffusion models, state-of-the-art image generation systems have generally been two-stage systems tha…
cs.AR2024
TATAA: Programmable Mixed-Precision Transformer Acceleration with a Transformable Arithmetic Architecture
Jiajun Wu, Mo Song, Jingmin Zhao +3
Modern transformer-based deep neural networks present unique technical challenges for effective acceleration in real-world applications. Apart from the vast amount of linear operat…