Research Paper#AI Acceleration, Diffusion Models, Transformer Networks🔬 ResearchAnalyzed: Jan 3, 2026 15:47
CorGi: Accelerating Diffusion Transformers with Caching
Published:Dec 30, 2025 12:55
•1 min read
•ArXiv
Analysis
This paper addresses the computational cost of Diffusion Transformers (DiT) in visual generation, a significant bottleneck. By introducing CorGi, a training-free method that caches and reuses transformer block outputs, the authors offer a practical solution to speed up inference without sacrificing quality. The focus on redundant computation and the use of contribution-guided caching are key innovations.
Key Takeaways
Reference
“CorGi and CorGi+ achieve up to 2.0x speedup on average, while preserving high generation quality.”