103 citations · 278 across the 43 of their papers we have counts for
5 papers · 1 filter
DeepCache: Accelerating Diffusion Models for Free
Xinyin Ma, Gongfan Fang, Xinchao Wang
Diffusion models have recently gained unprecedented attention in the field of image synthesis due to their remarkable generative capabilities. Notwithstanding their prowess, these…
SlimSAM: 0.1% Data Makes Segment Anything Slim
Zigeng Chen, Gongfan Fang, Xinyin Ma +1
Current approaches for compressing the Segment Anything Model (SAM) yield commendable results, yet necessitate extensive data to train a new network from scratch. Employing convent…
LLM-Pruner: On the Structural Pruning of Large Language Models
Xinyin Ma, Gongfan Fang, Xinchao Wang
Large language models (LLMs) have shown remarkable capabilities in language understanding and generation. However, such impressive capability typically comes with a substantial mod…
Structural Pruning for Diffusion Models
Gongfan Fang, Xinyin Ma, Xinchao Wang
Generative modeling has recently undergone remarkable advancements, primarily propelled by the transformative implications of Diffusion Probabilistic Models (DPMs). The impressive…
DepGraph: Towards Any Structural Pruning
Gongfan Fang, Xinyin Ma, Mingli Song +2
Structural pruning enables model acceleration by removing structurally-grouped parameters from neural networks. However, the parameter-grouping patterns vary widely across differen…