Fast-dLLM adds reusable KV cache blocks and selective parallel decoding to diffusion LLMs, closing most of the speed gap with autoregressive models without retraining.
Glide: Towards photorealistic image generation and editing with text-guided diffusion models, 2022
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
representative citing papers
VIPaint uses hierarchical variational inference to optimize a non-Gaussian Markov approximation of the diffusion posterior, enabling better inpainting and inverse problems with pre-trained and latent diffusion models.
citing papers explorer
-
Fast-dLLM: Training-free Acceleration of Diffusion LLM by Enabling KV Cache and Parallel Decoding
Fast-dLLM adds reusable KV cache blocks and selective parallel decoding to diffusion LLMs, closing most of the speed gap with autoregressive models without retraining.
-
VIPaint: Image Inpainting with Pre-Trained Diffusion Models via Variational Inference
VIPaint uses hierarchical variational inference to optimize a non-Gaussian Markov approximation of the diffusion posterior, enabling better inpainting and inverse problems with pre-trained and latent diffusion models.