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Direct Preference Optimization (DPO) has recently expanded its successful application from aligning large language models (LLMs) to aligning text-to-image models with human preferences, which has generated considerable interest within the community.
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Zero-shot text-to-image generation
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On decoding strategies for neural text generators
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Laion-5b: An open large-scale dataset for training next generation image-text models
A survey on video diffusion models
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Generative novel view synthesis with 3d-aware diffusion models
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Dall-e-bot: Introducing web-scale diffusion models to robotics
Ivan Kapelyukh, Vitalis Vosylius, and Edward Johns · 2023
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Training-free structured diffusion guidance for compositional text-to-image synthesis
Weixi Feng, Xuehai He, Tsu-Jui Fu, Varun Jampani, Arjun Reddy Akula, Pradyumna Narayana, Sugato Basu, Xin Eric Wang, and William Yang Wang · 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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Training a helpful and harmless assistant with reinforcement learning from human feedback
Yuntao Bai, Andy Jones, Kamal Ndousse, Amanda Askell, Anna Chen, Nova DasSarma, Dawn Drain, Stanislav Fort, Deep Ganguli, Tom Henighan, et al · 2022
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Compositional visual generation with composable diffusion models
Nan Liu, Shuang Li, Yilun Du, Antonio Torralba, and Joshua B Tenenbaum · 2022
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Scaling autoregressive models for content-rich text-to-image generation
Jiahui Yu, Yuanzhong Xu, Jing Yu Koh, Thang Luong, Gunjan Baid, Zirui Wang, Vijay Vasudevan, Alexander Ku, Yinfei Yang, Burcu Karagol Ayan, et al · 2022
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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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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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End-to-end diffusion latent optimization improves classifier guidance
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Sdxl: Improving latent diffusion models for high-resolution image synthesis
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Beyond reverse kl: Generalizing direct preference optimization with diverse divergence constraints
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Towards analyzing and understanding the limitations of dpo: A theoretical perspective
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3d-properties: Identifying challenges in dpo and charting a path forward
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Gemma: Open models based on gemini research and technology
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Baton: Aligning text-to-audio model with human preference feedback
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Directly fine-tuning diffusion models on differentiable rewards
Kevin Clark, Paul Vicol, Kevin Swersky, and David J Fleet · 2024
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Reinforcement learning for fine-tuning text-to-image diffusion models
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Evaluating text-to-visual generation with image-to-text generation
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