5 citations · 5 across the 2 of their papers we have counts for
2 papers
cs.CV2024
Scaling Diffusion Transformers to 16 Billion Parameters
Zhengcong Fei, Mingyuan Fan, Changqian Yu +2
In this paper, we present DiT-MoE, a sparse version of the diffusion Transformer, that is scalable and competitive with dense networks while exhibiting highly optimized inference.…
cs.CV2024★ 5 cited
Diffusion-RWKV: Scaling RWKV-Like Architectures for Diffusion Models
Zhengcong Fei, Mingyuan Fan, Changqian Yu +2
Transformers have catalyzed advancements in computer vision and natural language processing (NLP) fields. However, substantial computational complexity poses limitations for their…