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In robotic visuomotor policy learning, diffusion-based models have achieved significant success in improving the accuracy of action trajectory generation compared to traditional autoregressive models.
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Relay policy learning: Solving long-horizon tasks via imitation and reinforcement learning
Abhishek Gupta, Vikash Kumar, Corey Lynch, Sergey Levine, and Karol Hausman · 2019
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Semantic image synthesis with spatially-adaptive normalization
Taesung Park, Ming-Yu Liu, Ting-Chun Wang, and Jun-Yan Zhu · 2019
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Yi Zhou, Connelly Barnes, Jingwan Lu, Jimei Yang, and Hao Li · 2019
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An image is worth 16x16 words: Transformers for image recognition at scale
Dosovitskiy Alexey · 2020
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Language models are few-shot learners
Tom B Brown · 2020
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Recent advances in robot learning from demonstration
Harish chaandar Ravichandar, Athanasios S. Polydoros, Sonia Chernova, and Aude Billard · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Strictly batch imitation learning by energy-based distribution matching
Daniel Jarrett, Ioana Bica, and Mihaela van der Schaar · 2020
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Scaling laws for neural language models
Jared Kaplan, Sam McCandlish, Tom Henighan, Tom B Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei · 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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robosuite: A modular simulation framework and benchmark for robot learning
Yuke Zhu, Josiah Wong, Ajay Mandlekar, Roberto Martín-Martín, Abhishek Joshi, Soroush Nasiriany, Yifeng Zhu, and Kevin Lin · 2020
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Decision transformer: Reinforcement learning via sequence modeling
Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Misha Laskin, Pieter Abbeel, Aravind Srinivas, and Igor Mordatch · 2021
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Patrick Esser, Robin Rombach, and Bjorn Ommer · 2021
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Offline reinforcement learning as one big sequence modeling problem
Michael Janner, Qiyang Li, and Sergey Levine · 2021
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What matters in learning from offline human demonstrations for robot manipulation
Ajay Mandlekar, Danfei Xu, Josiah Wong, Soroush Nasiriany, Chen Wang, Rohun Kulkarni, Li Fei-Fei, Silvio Savarese, Yuke Zhu, and Roberto Martín-Martín · 2021
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Learning transferable visual models from natural language supervision
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Vector-quantized image modeling with improved vqgan
Jiahui Yu, Xin Li, Jing Yu Koh, Han Zhang, Ruoming Pang, James Qin, Alexander Ku, Yuanzhong Xu, Jason Baldridge, and Yonghui Wu · 2021
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Transporter networks: Rearranging the visual world for robotic manipulation
Andy Zeng, Pete Florence, Jonathan Tompson, Stefan Welker, Jonathan Chien, Maria Attarian, Travis Armstrong, Ivan Krasin, Dan Duong, Vikas Sindhwani, et al · 2021
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Do as i can, not as i say: Grounding language in robotic affordances
Michael Ahn, Anthony Brohan, Noah Brown, Yevgen Chebotar, Omar Cortes, Byron David, Chelsea Finn, Chuyuan Fu, Keerthana Gopalakrishnan, Karol Hausman, et al · 2022
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Is conditional generative modeling all you need for decision-making?
Yang Song, Prafulla Dhariwal, Mark Chen, and Ilya Sutskever · 2023
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Plex: Making the most of the available data for robotic manipulation pretraining
Garrett Thomas, Ching-An Cheng, Ricky Loynd, Felipe Vieira Frujeri, Vibhav Vineet, Mihai Jalobeanu, and Andrey Kolobov · 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
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From imitation to refinement–residual rl for precise assembly
Lars Ankile, Anthony Simeonov, Idan Shenfeld, Marcel Torne, and Pulkit Agrawal · 2024
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Dart: Denoising autoregressive transformer for scalable text-to-image generation
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Anurag Ajay, Yilun Du, Abhi Gupta, Joshua Tenenbaum, Tommi Jaakkola, and Pulkit Agrawal · 2022
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Flamingo: a visual language model for few-shot learning
Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, Antoine Miech, Iain Barr, Yana Hasson, Karel Lenc, Arthur Mensch, Katherine Millican, Malcolm Reynolds, et al · 2022
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From play to policy: Conditional behavior generation from uncurated robot data
Zichen Jeff Cui, Yibin Wang, Nur Muhammad Mahi Shafiullah, and Lerrel Pinto · 2022
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Implicit behavioral cloning
Pete Florence, Corey Lynch, Andy Zeng, Oscar A Ramirez, Ayzaan Wahid, Laura Downs, Adrian Wong, Johnny Lee, Igor Mordatch, and Jonathan Tompson · 2022
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Planning with diffusion for flexible behavior synthesis
Michael Janner, Yilun Du, Joshua Tenenbaum, and Sergey Levine · 2022
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Vima: General robot manipulation with multimodal prompts
Yunfan Jiang, Agrim Gupta, Zichen Zhang, Guanzhi Wang, Yongqiang Dou, Yanjun Chen, Li Fei-Fei, Anima Anandkumar, Yuke Zhu, and Linxi Fan · 2022
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Action chunking as policy compression
Lucy Lai, Ann Zixiang Huang, and Samuel J Gershman · 2022
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Autoregressive image generation using residual quantization
Doyup Lee, Chiheon Kim, Saehoon Kim, Minsu Cho, and Wook-Shin Han · 2022
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Jiatao Gu, Yuyang Wang, Yizhe Zhang, Qihang Zhang, Dinghuai Zhang, Navdeep Jaitly, Josh Susskind, and Shuangfei Zhai · 2024
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Openvla: An open-source vision-language-action model
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Manicm: Real-time 3d diffusion policy via consistency model for robotic manipulation
Guanxing Lu, Zifeng Gao, Tianxing Chen, Wenxun Dai, Ziwei Wang, and Yansong Tang · 2024
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Star: Scale-wise text-to-image generation via auto-regressive representations
Xiaoxiao Ma, Mohan Zhou, Tao Liang, Yalong Bai, Tiejun Zhao, Huaian Chen, and Yi Jin · 2024
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Consistency policy: Accelerated visuomotor policies via consistency distillation
Aaditya Prasad, Kevin Lin, Jimmy Wu, Linqi Zhou, and Jeannette Bohg · 2024
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Efficient autoregressive audio modeling via next-scale prediction
Kai Qiu, Xiang Li, Hao Chen, Jie Sun, Jinglu Wang, Zhe Lin, Marios Savvides, and Bhiksha Raj · 2024
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Multimodal diffusion transformer: Learning versatile behavior from multimodal goals
Moritz Reuss, Ömer Erdinç Yağmurlu, Fabian Wenzel, and Rudolf Lioutikov · 2024
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Germ: A generalist robotic model with mixture-of-experts for quadruped robot
Wenxuan Song, Han Zhao, Pengxiang Ding, Can Cui, Shangke Lyu, Yaning Fan, and Donglin Wang · 2024
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Autoregressive model beats diffusion: Llama for scalable image generation
Peize Sun, Yi Jiang, Shoufa Chen, Shilong Zhang, Bingyue Peng, Ping Luo, and Zehuan Yuan · 2024
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Visual autoregressive modeling: Scalable image generation via next-scale prediction
Keyu Tian, Yi Jiang, Zehuan Yuan, Bingyue Peng, and Liwei Wang · 2024
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Sparse diffusion policy: A sparse, reusable, and flexible policy for robot learning
Yixiao Wang, Yifei Zhang, Mingxiao Huo, Ran Tian, Xiang Zhang, Yichen Xie, Chenfeng Xu, Pengliang Ji, Wei Zhan, Mingyu Ding, et al · 2024
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Equibot: Sim (3)-equivariant diffusion policy for generalizable and data efficient learning
Jingyun Yang, Zi-ang Cao, Congyue Deng, Rika Antonova, Shuran Song, and Jeannette Bohg · 2024
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3d diffusion policy: Generalizable visuomotor policy learning via simple 3d representations
Yanjie Ze, Gu Zhang, Kangning Zhang, Chenyuan Hu, Muhan Wang, and Huazhe Xu · 2024
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Cobra: Extending mamba to multi-modal large language model for efficient inference
Han Zhao, Min Zhang, Wei Zhao, Pengxiang Ding, Siteng Huang, and Donglin Wang · 2024
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Quar-vla: Vision-language-action model for quadruped robots
Pengxiang Ding, Han Zhao, Wenjie Zhang, Wenxuan Song, Min Zhang, Siteng Huang, Ningxi Yang, and Donglin Wang · 2025
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Pite: Pixel-temporal alignment for large video-language model
Yang Liu, Pengxiang Ding, Siteng Huang, Min Zhang, Han Zhao, and Donglin Wang · 2025
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