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Diffusion models excel in generative tasks, but aligning them with specific objectives while maintaining their versatility remains challenging.
Elements of Sequential Monte Carlo
Christian A. Naesseth, Fredrik Lindsten, and Thomas B. Schön · 1903
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Fine-Tuning Language Models from Human Preferences, January 2020
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Pierre Del Moral, Arnaud Doucet, and Ajay Jasra · 2006
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Diffusion models beat gans on image synthesis
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Scaling Laws for Reward Model Overoptimization, October 2022
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Video Diffusion Models, June 2022
Jonathan Ho, Tim Salimans, Alexey Gritsenko, William Chan, Mohammad Norouzi, and David J. Fleet · 2022
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Tomasz Korbak, Hady Elsahar, Germán Kruszewski, and Marc Dymetman · 2022
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Repaint: Inpainting using denoising diffusion probabilistic models
Andreas Lugmayr, Martin Danelljan, Andres Romero, Fisher Yu, Radu Timofte, and Luc Van Gool · 2022
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Training language models to follow instructions with human feedback, March 2022
Long Ouyang, Jeff Wu, Xu Jiang, Diogo Almeida, Carroll L. Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul Christiano, Jan Leike, and Ryan Lowe · 2022
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High-resolution image synthesis with latent diffusion models
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Pseudoinverse-Guided Diffusion Models for Inverse Problems
Jiaming Song, Arash Vahdat, Morteza Mardani, and Jan Kautz · 2022
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Chain-of-thought prompting elicits reasoning in large language models
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Universal Guidance for Diffusion Models
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Training Diffusion Models with Reinforcement Learning
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Diffusion Posterior Sampling for General Noisy Inverse Problems
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Reward Model Ensembles Help Mitigate Overoptimization, March 2024
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DIFFUSION POSTERIOR SAMPLING FOR LINEAR INVERSE PROBLEM SOLVING — A FILTERING PERSPECTIVE
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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 · 2024
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Addressing negative transfer in diffusion models
Hyojun Go, Yunsung Lee, Seunghyun Lee, Shinhyeok Oh, Hyeongdon Moon, and Seungtaek Choi · 2024
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MANIFOLD PRESERVING GUIDED DIFFUSION
Yutong He, Naoki Murata, Chieh-Hsin Lai, Yuhta Takida, Toshimitsu Uesaka, Dongjun Kim, Wei-Hsiang Liao, Yuki Mitsufuji, J Zico Kolter, Ruslan Salakhutdinov, and Stefano Ermon · 2024
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Pick-a-pic: An open dataset of user preferences for text-to-image generation
Yuval Kirstain, Adam Polyak, Uriel Singer, Shahbuland Matiana, Joe Penna, and Omer Levy · 2023
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Aligning Text-to-Image Models using Human Feedback, February 2023
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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Probabilistic machine learning: Advanced topics
Kevin P Murphy · 2023
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Direct Preference Optimization: Your Language Model is Secretly a Reward Model
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Loss-guided diffusion models for plug-and-play controllable generation
Jiaming Song, Qinsheng Zhang, Hongxu Yin, Morteza Mardani, Ming-Yu Liu, Jan Kautz, Yongxin Chen, and Arash Vahdat · 2023
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ARGS: Alignment as reward-guided search
Maxim Khanov, Jirayu Burapacheep, and Yixuan Li · 2024
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Derivative-free guidance in continuous and discrete diffusion models with soft value-based decoding
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Sdxl: Improving latent diffusion models for high-resolution image synthesis
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Aligning Text-to-Image Diffusion Models with Reward Backpropagation, June 2024
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A diffusion model framework for unsupervised neural combinatorial optimization
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Laion aesthetic predictor
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Scaling llm test-time compute optimally can be more effective than scaling model parameters
Charlie Snell, Jaehoon Lee, Kelvin Xu, and Aviral Kumar · 2024
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Feedback Efficient Online Fine-Tuning of Diffusion Models
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Diffusion Model Alignment Using Direct Preference Optimization
Bram Wallace, Meihua Dang, Rafael Rafailov, Linqi Zhou, Aaron Lou, Senthil Purushwalkam, Stefano Ermon, Caiming Xiong, Shafiq Joty, and Nikhil Naik · 2024
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A closer look at time steps is worthy of triple speed-up for diffusion model training
Kai Wang, Mingjia Shi, Yukun Zhou, Zekai Li, Zhihang Yuan, Yuzhang Shang, Xiaojiang Peng, Hanwang Zhang, and Yang You · 2024
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Yangzhen Wu, Zhiqing Sun, Shanda Li, Sean Welleck, and Yiming Yang · 2024
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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 · 2024
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Confronting reward overoptimization for diffusion models: A perspective of inductive and primacy biases
Ziyi Zhang, Sen Zhang, Yibing Zhan, Yong Luo, Yonggang Wen, and Dacheng Tao · 2024
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Inference-time scaling for diffusion models beyond scaling denoising steps
Nanye Ma, Shangyuan Tong, Haolin Jia, Hexiang Hu, Yu-Chuan Su, Mingda Zhang, Xuan Yang, Yandong Li, Tommi Jaakkola, Xuhui Jia, et al · 2025
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Beta-tuned timestep diffusion model
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Human preference score: Better aligning text-to-image models with human preference
Xiaoshi Wu, Keqiang Sun, Feng Zhu, Rui Zhao, and Hongsheng Li · 2096
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