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Diffusion models have achieved remarkable success in text-to-image generation.
A meta-analysis of applications of diffusion models
Fareena Sultan, John U Farley, and Donald R Lehmann · 1990
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Reinforcement learning: A survey
Leslie Pack Kaelbling, Michael L Littman, and Andrew W Moore · 1996
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Policy invariance under reward transformations: Theory and application to reward shaping
Andrew Y Ng, Daishi Harada, and Stuart Russell · 1999
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Approximately optimal approximate reinforcement learning
Sham Kakade and John Langford · 2002
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Rethinking the inception architecture for computer vision, 2015
Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jonathon Shlens, and Zbigniew Wojna · 2015
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Visual relationship detection with language priors
Cewu Lu, Ranjay Krishna, Michael Bernstein, and Li Fei-Fei · 2016
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Hindsight experience replay
Marcin Andrychowicz, Filip Wolski, Alex Ray, Jonas Schneider, Rachel Fong, Peter Welinder, Bob McGrew, Josh Tobin, OpenAI Pieter Abbeel, and Wojciech Zaremba · 2017
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Deep reinforcement learning from human preferences
Paul F Christiano, Jan Leike, Tom Brown, Miljan Martic, Shane Legg, and Dario Amodei · 2017
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Survey of model-based reinforcement learning: Applications on robotics
Athanasios S Polydoros and Lazaros Nalpantidis · 2017
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Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
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A note on the inception score, 2018
Shane Barratt and Rishi Sharma · 2018
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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Online learning: A comprehensive survey, 2018
Steven C. H. Hoi, Doyen Sahoo, Jing Lu, and Peilin Zhao · 2018
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Data-efficient hierarchical reinforcement learning
Ofir Nachum, Shixiang Shane Gu, Honglak Lee, and Sergey Levine · 2018
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Learning by playing solving sparse reward tasks from scratch
Martin Riedmiller, Roland Hafner, Thomas Lampe, Michael Neunert, Jonas Degrave, Tom Wiele, Vlad Mnih, Nicolas Heess, and Jost Tobias Springenberg · 2018
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Variational information distillation for knowledge transfer, 2019
Sungsoo Ahn, Shell Xu Hu, Andreas Damianou, Neil D. Lawrence, and Zhenwen Dai · 2019
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Dealing with sparse rewards in reinforcement learning
Joshua Hare · 2019
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Decoupled weight decay regularization, 2019
Ilya Loshchilov and Frank Hutter · 2019
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Applications of deep reinforcement learning in communications and networking: A survey
Nguyen Cong Luong, Dinh Thai Hoang, Shimin Gong, Dusit Niyato, Ping Wang, Ying-Chang Liang, and Dong In Kim · 2019
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Keeping your distance: Solving sparse reward tasks using self-balancing shaped rewards
Alexander Trott, Stephan Zheng, Caiming Xiong, and Richard Socher · 2019
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Reinforcement learning for intelligent healthcare applications: A survey
Antonio Coronato, Muddasar Naeem, Giuseppe De Pietro, and Giovanni Paragliola · 2020
Cited alongside, same era.
Generative adversarial networks
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2020
Cited alongside, same era.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Cited alongside, same era.
Learning to utilize shaping rewards: A new approach of reward shaping
Yujing Hu, Weixun Wang, Hangtian Jia, Yixiang Wang, Yingfeng Chen, Jianye Hao, Feng Wu, and Changjie Fan · 2020
Cited alongside, same era.
Monte carlo gradient estimation in machine learning
Shakir Mohamed, Mihaela Rosca, Michael Figurnov, and Andriy Mnih · 2020
Cited alongside, same era.
Improved techniques for training score-based generative models
Yang Song and Stefano Ermon · 2020
Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al · 2023
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Improving image generation with better captions
James Betker, Gabriel Goh, Li Jing, Tim Brooks, Jianfeng Wang, Linjie Li, Long Ouyang, Juntang Zhuang, Joyce Lee, Yufei Guo, et al · 2023
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Renaissance: A survey into ai text-to-image generation in the era of large model, 2023
Fengxiang Bie, Yibo Yang, Zhongzhu Zhou, Adam Ghanem, Minjia Zhang, Zhewei Yao, Xiaoxia Wu, Connor Holmes, Pareesa Golnari, David A. Clifton, Yuxiong He, Dacheng Tao, and Shuaiwen Leon Song · 2023
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Training diffusion models with reinforcement learning
Kevin Black, Michael Janner, Yilun Du, Ilya Kostrikov, and Sergey Levine · 2023
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Diffusion self-guidance for controllable image generation
Dave Epstein, Allan Jabri, Ben Poole, Alexei Efros, and Aleksander Holynski · 2023
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Cited alongside, same era.
Differentiable augmentation for data-efficient gan training
Shengyu Zhao, Zhijian Liu, Ji Lin, Jun-Yan Zhu, and Song Han · 2020
Cited alongside, same era.
Conditional image generation with score-based diffusion models
Georgios Batzolis, Jan Stanczuk, Carola-Bibiane Schönlieb, and Christian Etmann · 2021
Cited alongside, same era.
Diffusion models beat GANs on image synthesis
Prafulla Dhariwal and Alexander Quinn Nichol · 2021
Cited alongside, same era.
Deberta: Decoding-enhanced bert with disentangled attention
Pengcheng He, Xiaodong Liu, Jianfeng Gao, and Weizhu Chen · 2021
Cited alongside, same era.
Classifier-free diffusion guidance
Jonathan Ho and Tim Salimans · 2021
Cited alongside, same era.
Lora: Low-rank adaptation of large language models, 2021
Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen · 2021
Cited alongside, same era.
Dpok: Reinforcement learning for fine-tuning text-to-image diffusion models
Ying Fan, Olivia Watkins, Yuqing Du, Hao Liu, Moonkyung Ryu, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh, Kangwook Lee, and Kimin Lee · 2023
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Multi-concept customization of text-to-image diffusion
Nupur Kumari, Bingliang Zhang, Richard Zhang, Eli Shechtman, and Jun-Yan Zhu · 2023
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Aligning text-to-image models using human feedback
Kimin Lee, Hao Liu, Moonkyung Ryu, Olivia Watkins, Yuqing Du, Craig Boutilier, Pieter Abbeel, Mohammad Ghavamzadeh, and Shixiang Shane Gu · 2023
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Aligning text-to-image diffusion models with reward backpropagation
Mihir Prabhudesai, Anirudh Goyal, Deepak Pathak, and Katerina Fragkiadaki · 2023
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Direct preference optimization: Your language model is secretly a reward model, 2023
Rafael Rafailov, Archit Sharma, Eric Mitchell, Stefano Ermon, Christopher D. Manning, and Chelsea Finn · 2023
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Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation
Nataniel Ruiz, Yuanzhen Li, Varun Jampani, Yael Pritch, Michael Rubinstein, and Kfir Aberman · 2023
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Cads: Unleashing the diversity of diffusion models through condition-annealed sampling
Seyedmorteza Sadat, Jakob Buhmann, Derek Bradely, Otmar Hilliges, and Romann M Weber · 2023
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Diffusion model alignment using direct preference optimization, 2023
Bram Wallace, Meihua Dang, Rafael Rafailov, Linqi Zhou, Aaron Lou, Senthil Purushwalkam, Stefano Ermon, Caiming Xiong, Shafiq Joty, and Nikhil Naik · 2023
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Imagereward: Learning and evaluating human preferences for text-to-image generation
Jiazheng Xu, Xiao Liu, Yuchen Wu, Yuxuan Tong, Qinkai Li, Ming Ding, Jie Tang, and Yuxiao Dong · 2023
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Diffusion models: A comprehensive survey of methods and applications
Ling Yang, Zhilong Zhang, Yang Song, Shenda Hong, Runsheng Xu, Yue Zhao, Wentao Zhang, Bin Cui, and Ming-Hsuan Yang · 2023
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Directly fine-tuning diffusion models on differentiable rewards, 2024
Kevin Clark, Paul Vicol, Kevin Swersky, and David J Fleet · 2024
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Comat: Aligning text-to-image diffusion model with image-to-text concept matching
Dongzhi Jiang, Guanglu Song, Xiaoshi Wu, Renrui Zhang, Dazhong Shen, Zhuofan Zong, Yu Liu, and Hongsheng Li · 2024
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Aligning diffusion models by optimizing human utility, 2024
Shufan Li, Konstantinos Kallidromitis, Akash Gokul, Yusuke Kato, and Kazuki Kozuka · 2024
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Patch diffusion: Faster and more data-efficient training of diffusion models
Zhendong Wang, Yifan Jiang, Huangjie Zheng, Peihao Wang, Pengcheng He, Zhangyang Wang, Weizhu Chen, Mingyuan Zhou, et al · 2024
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Inherent trade-offs between diversity and stability in multi-task benchmark
Guanhua Zhang and Moritz Hardt · 2024
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