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Conventional flow matching and diffusion-based policies sample via iterative denoising from standard noise distributions (e.g., Gaussian), and require conditioning modules to repeatedly incorporate visual information during the generative process, incurring substantial time and memory overhead.
Auto-encoding variational bayes, 2013
Diederik P Kingma, Max Welling, et al · 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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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Film: Visual reasoning with a general conditioning layer
Ethan Perez, Florian Strub, Harm De Vries, Vincent Dumoulin, and Aaron Courville · 2018
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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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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Video diffusion models
Jonathan Ho, Tim Salimans, Alexey Gritsenko, William Chan, Mohammad Norouzi, and David J Fleet · 2022
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Flow straight and fast: Learning to generate and transfer data with rectified flow, 2022
Xingchao Liu, Chengyue Gong, and Qiang Liu · 2022
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Building normalizing flows with stochastic interpolants
Michael S Albergo and Eric Vanden-Eijnden · 2022
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Flow straight and fast: Learning to generate and transfer data with rectified flow
Xingchao Liu, Chengyue Gong, and Qiang Liu · 2022
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Flow straight and fast: Learning to generate and transfer data with rectified flow
Xingchao Liu, Chengyue Gong, and Qiang Liu · 2022
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Scalable diffusion models with transformers
William Peebles and Saining Xie · 2023
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Adding conditional control to text-to-image diffusion models
Lvmin Zhang, Anyi Rao, and Maneesh Agrawala · 2023
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Videogen: A reference-guided latent diffusion approach for high definition text-to-video generation
Xin Li, Wenqing Chu, Ye Wu, Weihang Yuan, Fanglong Liu, Qi Zhang, Fu Li, Haocheng Feng, Errui Ding, and Jingdong Wang · 2023
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Diffusion policy: Visuomotor policy learning via action diffusion
Cheng Chi, Zhenjia Xu, Siyuan Feng, Eric Cousineau, Yilun Du, Benjamin Burchfiel, Russ Tedrake, and Shuran Song · 2023
Cited alongside, same era.
Flow matching for generative modeling, 2023
Yaron Lipman, Ricky T. Q. Chen, Heli Ben-Hamu, Maximilian Nickel, and Matt Le · 2023
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Discovering failure modes of text-guided diffusion models via adversarial search
Qihao Liu, Adam Kortylewski, Yutong Bai, Song Bai, and Alan Yuille · 2023
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Learning fine-grained bimanual manipulation with low-cost hardware
Tony Z Zhao, Vikash Kumar, Sergey Levine, and Chelsea Finn · 2023
Cited alongside, same era.
Simulation-free schr \ \backslash " odinger bridges via score and flow matching
Alexander Tong, Nikolay Malkin, Kilian Fatras, Lazar Atanackovic, Yanlei Zhang, Guillaume Huguet, Guy Wolf, and Yoshua Bengio · 2023
Active vision might be all you need: Exploring active vision in bimanual robotic manipulation
Ian Chuang, Andrew Lee, Dechen Gao, M Naddaf-Sh, Iman Soltani, et al · 2024
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Mobile aloha: Learning bimanual mobile manipulation using low-cost whole-body teleoperation
Zipeng Fu, Tony Z Zhao, and Chelsea Finn · 2024
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Aloha unleashed: A simple recipe for robot dexterity
Tony Z Zhao, Jonathan Tompson, Danny Driess, Pete Florence, Kamyar Ghasemipour, Chelsea Finn, and Ayzaan Wahid · 2024
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Andrew Lee, Ian Chuang, Ling-Yuan Chen, and Iman Soltani · 2024
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Cited alongside, same era.
Boosting latent diffusion with flow matching
Johannes S Fischer, Ming Gui, Pingchuan Ma, Nick Stracke, Stefan A Baumann, and Björn Ommer · 2023
Cited alongside, same era.
Simulation-free schr \ \backslash " odinger bridges via score and flow matching
Alexander Tong, Nikolay Malkin, Kilian Fatras, Lazar Atanackovic, Yanlei Zhang, Guillaume Huguet, Guy Wolf, and Yoshua Bengio · 2023
Cited alongside, same era.
Improving and generalizing flow-based generative models with minibatch optimal transport
Alexander Tong, Kilian Fatras, Nikolay Malkin, Guillaume Huguet, Yanlei Zhang, Jarrid Rector-Brooks, Guy Wolf, and Yoshua Bengio · 2023
Cited alongside, same era.
Sit: Exploring flow and diffusion-based generative models with scalable interpolant transformers
Nanye Ma, Mark Goldstein, Michael S Albergo, Nicholas M Boffi, Eric Vanden-Eijnden, and Saining Xie · 2024
Cited alongside, same era.
Flowing from words to pixels: A framework for cross-modality evolution
Qihao Liu, Xi Yin, Alan Yuille, Andrew Brown, and Mannat Singh · 2024
Cited alongside, same era.
Pyramidal flow matching for efficient video generative modeling
Yang Jin, Zhicheng Sun, Ningyuan Li, Kun Xu, Hao Jiang, Nan Zhuang, Quzhe Huang, Yang Song, Yadong Mu, and Zhouchen Lin · 2024
Cited alongside, same era.
Diffusion policy policy optimization
Allen Z Ren, Justin Lidard, Lars L Ankile, Anthony Simeonov, Pulkit Agrawal, Anirudha Majumdar, Benjamin Burchfiel, Hongkai Dai, and Max Simchowitz · 2024
Cited alongside, same era.
Fan Zhang and Michael Gienger · 2024
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In-context imitation learning via next-token prediction
Letian Fu, Huang Huang, Gaurav Datta, Lawrence Yunliang Chen, William Chung-Ho Panitch, Fangchen Liu, Hui Li, and Ken Goldberg · 2024
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Carp: Visuomotor policy learning via coarse-to-fine autoregressive prediction
Zhefei Gong, Pengxiang Ding, Shangke Lyu, Siteng Huang, Mingyang Sun, Wei Zhao, Zhaoxin Fan, and Donglin Wang · 2024
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Simulation-free schrödinger bridges via score and flow matching, 2024
Alexander Tong, Nikolay Malkin, Kilian Fatras, Lazar Atanackovic, Yanlei Zhang, Guillaume Huguet, Guy Wolf, and Yoshua Bengio · 2024
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Scaling rectified flow transformers for high-resolution image synthesis, 2024
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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Alleviating distortion in image generation via multi-resolution diffusion models and time-dependent layer normalization
Qihao Liu, Zhanpeng Zeng, Ju He, Qihang Yu, Xiaohui Shen, and Liang-Chieh Chen · 2024
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Flowar: Scale-wise autoregressive image generation meets flow matching
Sucheng Ren, Qihang Yu, Ju He, Xiaohui Shen, Alan Yuille, and Liang-Chieh Chen · 2024
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Rdt-1b: a diffusion foundation model for bimanual manipulation
Songming Liu, Lingxuan Wu, Bangguo Li, Hengkai Tan, Huayu Chen, Zhengyi Wang, Ke Xu, Hang Su, and Jun Zhu · 2024
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Flowtok: Flowing seamlessly across text and image tokens
Ju He, Qihang Yu, Qihao Liu, and Liang-Chieh Chen · 2025
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In-ril: Interleaved reinforcement and imitation learning for policy fine-tuning
Dechen Gao, Hang Wang, Hanchu Zhou, Nejib Ammar, Shatadal Mishra, Ahmadreza Moradipari, Iman Soltani, and Junshan Zhang · 2025
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Dense policy: Bidirectional autoregressive learning of actions
Yue Su, Xinyu Zhan, Hongjie Fang, Han Xue, Hao-Shu Fang, Yong-Lu Li, Cewu Lu, and Lixin Yang · 2025
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Flowpolicy: Enabling fast and robust 3d flow-based policy via consistency flow matching for robot manipulation
Qinglun Zhang, Zhen Liu, Haoqiang Fan, Guanghui Liu, Bing Zeng, and Shuaicheng Liu · 2025
Closest in time.