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Direct Preference Optimization (DPO) has emerged as a powerful approach to align text-to-image (T2I) models with human feedback.
Rank analysis of incomplete block designs: I. the method of paired comparisons
Ralph Allan Bradley and Milton E Terry · 1952
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Simple statistical gradient-following algorithms for connectionist reinforcement learning
Ronald J Williams · 1992
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Learning to rank with nonsmooth cost functions
Christopher Burges, Robert Ragno, and Quoc Le · 2006
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Policy shaping: Integrating human feedback with reinforcement learning
Shane Griffith, Kaushik Subramanian, Jonathan Scholz, Charles L Isbell, and Andrea L Thomaz · 2013
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A theoretical analysis of ndcg type ranking measures
Yining Wang, Liwei Wang, Yuanzhi Li, Di He, and Tie-Yan Liu · 2013
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Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
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Generative adversarial text to image synthesis
Scott Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, and Honglak Lee · 2016
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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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Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
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Stackgan: Text to photo-realistic image synthesis with stacked generative adversarial networks
Han Zhang, Tao Xu, Hongsheng Li, Shaoting Zhang, Xiaogang Wang, Xiaolei Huang, and Dimitris Metaxas · 2017
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The lambdaloss framework for ranking metric optimization
Xuanhui Wang, Cheng Li, Nadav Golbandi, Michael Bendersky, and Marc Najork · 2018
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu · 2020
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Per-pixel classification is not all you need for semantic segmentation
Bowen Cheng, Alex Schwing, and Alexander Kirillov · 2021
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Clipscore: A reference-free evaluation metric for image captioning
Jack Hessel, Ari Holtzman, Maxwell Forbes, Ronan Le Bras, and Yejin Choi · 2021
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
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Laion-5b: An open large-scale dataset for training next generation image-text models
Christoph Schuhmann, Romain Beaumont, Richard Vencu, Cade Gordon, Ross Wightman, Mehdi Cherti, Theo Coombes, Aarush Katta, Clayton Mullis, Mitchell Wortsman, et al · 2022
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Building normalizing flows with stochastic interpolants
Michael S Albergo and Eric Vanden-Eijnden · 2023
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All are worth words: A vit backbone for diffusion models
Fan Bao, Shen Nie, Kaiwen Xue, Yue Cao, Chongxuan Li, Hang Su, and Jun Zhu · 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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Emu: Enhancing image generation models using photogenic needles in a haystack
Xiaoliang Dai, Ji Hou, Chih-Yao Ma, Sam Tsai, Jialiang Wang, Rui Wang, Peizhao Zhang, Simon Vandenhende, Xiaofang Wang, Abhimanyu Dubey, et al · 2023
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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 · 2023
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Datacomp: In search of the next generation of multimodal datasets
Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang, Jonathan Hayase, Georgios Smyrnis, Thao Nguyen, Ryan Marten, Mitchell Wortsman, Dhruba Ghosh, Jieyu Zhang, et al · 2023
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Geneval: An object-focused framework for evaluating text-to-image alignment
Dhruba Ghosh, Hanna Hajishirzi, and Ludwig Schmidt · 2023
Cited alongside, same era.
T2i-compbench: A comprehensive benchmark for open-world compositional text-to-image generation
Kaiyi Huang, Kaiyue Sun, Enze Xie, Zhenguo Li, and Xihui Liu · 2023
Directly fine-tuning diffusion models on differentiable rewards
Kevin Clark, Paul Vicol, Kevin Swersky, and David J Fleet · 2024
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Reward model ensembles help mitigate overoptimization
Thomas Coste, Usman Anwar, Robert Kirk, and David Krueger · 2024
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Prdp: Proximal reward difference prediction for large-scale reward finetuning of diffusion models
Fei Deng, Qifei Wang, Wei Wei, Matthias Grundmann, and Tingbo Hou · 2024
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Carles Domingo-Enrich, Michal Drozdzal, Brian Karrer, and Ricky TQ Chen · 2024
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Scaling rectified flow transformers for high-resolution image synthesis
Patrick Esser, Sumith Kulal, Andreas Blattmann, Rahim Entezari, Jonas Müller, Harry Saini, Yam Levi, Dominik Lorenz, Axel Sauer, Frederic Boesel, et al · 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
Cited alongside, same era.
Flow matching for generative modeling
Yaron Lipman, Ricky TQ Chen, Heli Ben-Hamu, Maximilian Nickel, and Matt Le · 2023
Cited alongside, same era.
Visual instruction tuning
Haotian Liu, Chunyuan Li, Qingyang Wu, and Yong Jae Lee · 2023
Cited alongside, same era.
Toward verifiable and reproducible human evaluation for text-to-image generation
Mayu Otani, Riku Togashi, Yu Sawai, Ryosuke Ishigami, Yuta Nakashima, Esa Rahtu, Janne Heikkilä, and Shin’ichi Satoh · 2023
Cited alongside, same era.
Scalable diffusion models with transformers
William Peebles and Saining Xie · 2023
Cited alongside, same era.
Sdxl: Improving latent diffusion models for high-resolution image synthesis, 2023
Dustin Podell, Zion English, Kyle Lacey, Andreas Blattmann, Tim Dockhorn, Jonas Müller, Joe Penna, and Robin Rombach · 2023
Cited alongside, same era.
Aligning text-to-image diffusion models with reward backpropagation
Mihir Prabhudesai, Anirudh Goyal, Deepak Pathak, and Katerina Fragkiadaki · 2023
Cited alongside, same era.
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Kto: Model alignment as prospect theoretic optimization
Kawin Ethayarajh, Winnie Xu, Niklas Muennighoff, Dan Jurafsky, and Douwe Kiela · 2024
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Reno: Enhancing one-step text-to-image models through reward-based noise optimization
Luca Eyring, Shyamgopal Karthik, Karsten Roth, Alexey Dosovitskiy, and Zeynep Akata · 2024
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Diffusion-rpo: Aligning diffusion models through relative preference optimization
Yi Gu, Zhendong Wang, Yueqin Yin, Yujia Xie, and Mingyuan Zhou · 2024
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Ella: Equip diffusion models with llm for enhanced semantic alignment
Xiwei Hu, Rui Wang, Yixiao Fang, Bin Fu, Pei Cheng, and Gang Yu · 2024
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Elucidating optimal reward-diversity tradeoffs in text-to-image diffusion models
Rohit Jena, Ali Taghibakhshi, Sahil Jain, Gerald Shen, Nima Tajbakhsh, and Arash Vahdat · 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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Fine-tuning diffusion models for enhancing face quality in text-to-image generation
Zhenyi Liao, Qingsong Xie, Chen Chen, Hannan Lu, and Zhijie Deng · 2024
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Evaluating text-to-visual generation with image-to-text generation
Zhiqiu Lin, Deepak Pathak, Baiqi Li, Jiayao Li, Xide Xia, Graham Neubig, Pengchuan Zhang, and Deva Ramanan · 2024
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Exploring the role of large language models in prompt encoding for diffusion models
Bingqi Ma, Zhuofan Zong, Guanglu Song, Hongsheng Li, and Yu Liu · 2024
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Simpo: Simple preference optimization with a reference-free reward
Yu Meng, Mengzhou Xia, and Danqi Chen · 2024
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Würstchen: An efficient architecture for large-scale text-to-image diffusion models
Pablo Pernias, Dominic Rampas, Mats L Richter, Christopher J Pal, and Marc Aubreville · 2024
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Video diffusion alignment via reward gradients
Mihir Prabhudesai, Russell Mendonca, Zheyang Qin, Katerina Fragkiadaki, and Deepak Pathak · 2024
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Preference ranking optimization for human alignment
Feifan Song, Bowen Yu, Minghao Li, Haiyang Yu, Fei Huang, Yongbin Li, and Houfeng Wang · 2024
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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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Simple multi-dataset detection
Xingyi Zhou, Vladlen Koltun, and Philipp Krähenbühl · 2024
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