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Ablating Concepts in Text-to-Image Diffusion Models
Nupur Kumari,
Bingliang Zhang,
Sheng-Yu Wang,
Eli Shechtman,
Richard Zhang,
Jun-Yan Zhu,
arXiv  / 
code
An efficient method for ablating previously learnt concepts by providing the natural language description. The concept can be a type of artistic style, an object instance or a specific memorized image.
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Multi-concept Customization of Text-to-Image Diffusion
Nupur Kumari,
Bingliang Zhang,
Richard Zhang,
Eli Shechtman,
Jun-Yan Zhu,
CVPR, 2023
arXiv  / 
code
An efficient method for augmenting existing text-to-image models to learn new concepts with few examples without forgeting learned knowledge. Also we propose a close-form optimization strategy for combining learned weights of multiple concepts.
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Continuously Discovering Novel Strategies via Reward-Switching Policy Optimization
Zihan Zhou,
Wei Fu,
Bingliang Zhang,
Yi Wu,
ICLR, 2022
arXiv
A paradigm to discover diverse strategies in complex RL environments. Our method is able to discover a wide spectrum of strategies in a variety of domains.
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