34 citations · 76 across the 3 of their papers we have counts for
3 papers
cs.CV2023★ 21 cited
FastComposer: Tuning-Free Multi-Subject Image Generation with Localized Attention
Guangxuan Xiao, Tianwei Yin, William T. Freeman +2
Diffusion models excel at text-to-image generation, especially in subject-driven generation for personalized images. However, existing methods are inefficient due to the subject-sp…
cs.CL2023★ 21 cited
Offsite-Tuning: Transfer Learning without Full Model
Guangxuan Xiao, Ji Lin, Song Han
Transfer learning is important for foundation models to adapt to downstream tasks. However, many foundation models are proprietary, so users must share their data with model owners…
cs.LG2019★ 34 cited
Defensive Quantization: When Efficiency Meets Robustness
Ji Lin, Chuang Gan, Song Han
Neural network quantization is becoming an industry standard to efficiently deploy deep learning models on hardware platforms, such as CPU, GPU, TPU, and FPGAs. However, we observe…