4 citations · 6 across the 6 of their papers we have counts for
Showing 2026Show all
3 papers · 1 filter
cs.CV2026
Hybrid-Basis Feature Forecasting for Diffusion Sampling Acceleration
Kai-Liang Cheng, Yuan-Yuan Cheng, Yu-fan Jin +1
We propose Hybrid-Basis Feature Forecasting (HybridFF), a training-free, plug-and-play framework for accelerating diffusion sampling. To capture local smoothness, long-range trends…
cs.AI2026
Source-Prior-Driven Selective Adaptation for Efficient Diffusion Model Finetuning
Yi Xiong, Yuan-Yuan Cheng, Xiao-Ming Fu
Fine-tuning large diffusion models for new domains or styles involves a trade-off: improving target-specific generation often degrades the pretrained model's broad generative capab…
cs.GR2026
BRepMAE: Self-Supervised Masked BRep Autoencoders for Machining Feature Recognition
Can Yao, Kang Wu, Zuheng Zheng +2
We propose a masked self-supervised learning framework, called BRepMAE, for automatically extracting a valuable representation of the input computer-aided design (CAD) model to rec…