This paper fixes a hidden mismatch in image generation: tokenizers make tokens without order, but generators need an order to predict the next token well.

#visual tokenization#autoregressive image generation#causal dependencies

YOLO-Master: MOE-Accelerated with Specialized Transformers for Enhanced Real-time Detection

Intermediate

Xu Lin, Jinlong Peng et al.Dec 29arXiv

YOLO-Master is a new real-time object detector that uses a Mixture-of-Experts (MoE) design to spend more compute on hard scenes and less on easy ones.

#YOLO-Master#Mixture of Experts#ES-MoE

SonicMoE: Accelerating MoE with IO and Tile-aware Optimizations

Intermediate

Wentao Guo, Mayank Mishra et al.Dec 16arXiv

SonicMoE makes Mixture-of-Experts (MoE) models train faster and use less memory by redesigning how data is moved and computed on GPUs.

#Mixture of Experts#Grouped GEMM#Token Rounding