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Generalist robot policies, trained on large and diverse datasets, have demonstrated the ability to generalize across a wide spectrum of behaviors, enabling a single policy to act in varied real-world environments.
A framework for behavioural cloning
Michael Bain and Claude Sammut · 1995
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Overcoming catastrophic forgetting in neural networks
James Kirkpatrick, Razvan Pascanu, Neil Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, et al · 2017
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Gradient episodic memory for continual learning
David Lopez-Paz and Marc’Aurelio Ranzato · 2017
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Progress & compress: A scalable framework for continual learning
Jonathan Schwarz, Wojciech Czarnecki, Jelena Luketina, Agnieszka Grabska-Barwinska, Yee Whye Teh, Razvan Pascanu, and Raia Hadsell · 2018
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Policy consolidation for continual reinforcement learning
Christos Kaplanis, Murray Shanahan, and Claudia Clopath · 2019
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Continual learning for robotics: Definition, framework, learning strategies, opportunities and challenges
Timothée Lesort, Vincenzo Lomonaco, Andrei Stoian, Davide Maltoni, David Filliat, and Natalia Díaz-Rodríguez · 2020
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What is being transferred in transfer learning?
Behnam Neyshabur, Hanie Sedghi, and Chiyuan Zhang · 2020
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Encoding primitives generation policy learning for robotic arm to overcome catastrophic forgetting in sequential multi-tasks learning
Fangzhou Xiong, Zhiyong Liu, Kaizhu Huang, Xu Yang, Hong Qiao, and Amir Hussain · 2020
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Continual world: A robotic benchmark for continual reinforcement learning
Maciej Wołczyk, Michał Zając, Razvan Pascanu, Łukasz Kuciński, and Piotr Miłoś · 2021
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Lora: Low-rank adaptation of large language models
Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, Weizhu Chen, et al · 2022
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Patching open-vocabulary models by interpolating weights
Gabriel Ilharco, Mitchell Wortsman, Samir Yitzhak Gadre, Shuran Song, Hannaneh Hajishirzi, Simon Kornblith, Ali Farhadi, and Ludwig Schmidt · 2022
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Dataless knowledge fusion by merging weights of language models
Xisen Jin, Xiang Ren, Daniel Preotiuc-Pietro, and Pengxiang Cheng · 2022
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Transformer adapters for robot learning
Anthony Liang, Ishika Singh, Karl Pertsch, and Jesse Thomason · 2022
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Merging models with fisher-weighted averaging
Michael S Matena and Colin A Raffel · 2022
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Rohan Anil, Andrew M Dai, Orhan Firat, Melvin Johnson, Dmitry Lepikhin, Alexandre Passos, Siamak Shakeri, Emanuel Taropa, Paige Bailey, Zhifeng Chen, et al · 2023
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Continual learning from demonstration of robotics skills
Sayantan Auddy, Jakob Hollenstein, Matteo Saveriano, Antonio Rodríguez-Sánchez, and Justus Piater · 2023
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Zero-shot robotic manipulation with pretrained image-editing diffusion models
Kevin Black, Mitsuhiko Nakamoto, Pranav Atreya, Homer Walke, Chelsea Finn, Aviral Kumar, and Sergey Levine · 2023
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Robocat: A self-improving foundation agent for robotic manipulation
Konstantinos Bousmalis, Giulia Vezzani, Dushyant Rao, Coline Devin, Alex X Lee, Maria Bauza, Todor Davchev, Yuxiang Zhou, Agrim Gupta, Akhil Raju, et al · 2023
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Rt-2: Vision-language-action models transfer web knowledge to robotic control
Anthony Brohan, Noah Brown, Justice Carbajal, Yevgen Chebotar, Xi Chen, Krzysztof Choromanski, Tianli Ding, Danny Driess, Avinava Dubey, Chelsea Finn, et al · 2023
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Tail: Task-specific adapters for imitation learning with large pretrained models
Zuxin Liu, Jesse Zhang, Kavosh Asadi, Yao Liu, Ding Zhao, Shoham Sabach, and Rasool Fakoor · 2023
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Parameter-efficient tuning of pretrained visual-language models in multitask robot learning
Marcel Mittenbuehler, Ahmed Hendawy, Carlo D’Eramo, and Georgia Chalvatzaki · 2023
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Gnm: A general navigation model to drive any robot
Dhruv Shah, Ajay Sridhar, Arjun Bhorkar, Noriaki Hirose, and Sergey Levine · 2023
Cited alongside, same era.
Lossless adaptation of pretrained vision models for robotic manipulation
Mohit Sharma, Claudio Fantacci, Yuxiang Zhou, Skanda Koppula, Nicolas Heess, Jon Scholz, and Yusuf Aytar · 2023
Cited alongside, same era.
Bridgedata v2: A dataset for robot learning at scale
Homer Rich Walke, Kevin Black, Tony Z Zhao, Quan Vuong, Chongyi Zheng, Philippe Hansen-Estruch, Andre Wang He, Vivek Myers, Moo Jin Kim, Max Du, et al · 2023
Cited alongside, same era.
Hyper-decision transformer for efficient online policy adaptation
Mengdi Xu, Yuchen Lu, Yikang Shen, Shun Zhang, Ding Zhao, and Chuang Gan · 2023
Cited alongside, same era.
Ties-merging: Resolving interference when merging models
Prateek Yadav, Derek Tam, Leshem Choshen, Colin A Raffel, and Mohit Bansal · 2023
Cited alongside, same era.
Active fine-tuning of multi-task policies
Marco Bagatella, Jonas Hübotter, Georg Martius, and Andreas Krause · 2025
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Datamil: Selecting data for robot imitation learning with datamodels
Shivin Dass, Alaa Khaddaj, Logan Engstrom, Aleksander Madry, Andrew Ilyas, and Roberto Martín-Martín · 2025
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A taxonomy for evaluating generalist robot policies
Jensen Gao, Suneel Belkhale, Sudeep Dasari, Ashwin Balakrishna, Dhruv Shah, and Dorsa Sadigh · 2025
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Dongchi Huang, Zhirui Fang, Tianle Zhang, Yihang Li, Lin Zhao, and Chunhe Xia · 2025
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π \pi 0. 5: a vision-language-action model with open-world generalization, 2025
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π 0 \pi_{0} : A vision-language-action flow model for general robot control
Kevin Black, Noah Brown, Danny Driess, Adnan Esmail, Michael Equi, Chelsea Finn, Niccolo Fusai, Lachy Groom, Karol Hausman, Brian Ichter, et al · 2024
Cited alongside, same era.
Dinobot: Robot manipulation via retrieval and alignment with vision foundation models
Norman Di Palo and Edward Johns · 2024
Cited alongside, same era.
Jiaheng Hu, Rose Hendrix, Ali Farhadi, Aniruddha Kembhavi, Roberto Martín-Martín, Peter Stone, Kuo-Hao Zeng, and Kiana Ehsani · 2024
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Model stock: All we need is just a few fine-tuned models
Dong-Hwan Jang, Sangdoo Yun, and Dongyoon Han · 2024
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Droid: A large-scale in-the-wild robot manipulation dataset
Alexander Khazatsky, Karl Pertsch, Suraj Nair, Ashwin Balakrishna, Sudeep Dasari, Siddharth Karamcheti, Soroush Nasiriany, Mohan Kumar Srirama, Lawrence Yunliang Chen, Kirsty Ellis, et al · 2024
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Openvla: An open-source vision-language-action model
Moo Jin Kim, Karl Pertsch, Siddharth Karamcheti, Ted Xiao, Ashwin Balakrishna, Suraj Nair, Rafael Rafailov, Ethan Foster, Grace Lam, Pannag Sanketi, et al · 2024
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Policy agnostic rl: Offline rl and online rl fine-tuning of any class and backbone
Max Sobol Mark, Tian Gao, Georgia Gabriela Sampaio, Mohan Kumar Srirama, Archit Sharma, Chelsea Finn, and Aviral Kumar · 2024
Cited alongside, same era.
Physical Intelligence, Kevin Black, Noah Brown, James Darpinian, Karan Dhabalia, Danny Driess, Adnan Esmail, Michael Equi, Chelsea Finn, Niccolo Fusai, et al · 2025
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Fine-tuning vision-language-action models: Optimizing speed and success
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Fine-tuning large language models for domain adaptation: Exploration of training strategies, scaling, model merging and synergistic capabilities
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Model merging improves zero-shot generalization in bioacoustic foundation models
Davide Marincione, Donato Crisostomi, Roberto Dessi, Emanuele Rodolà, and Emanuele Rossi · 2025
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Preserving and combining knowledge in robotic lifelong reinforcement learning
Yuan Meng, Zhenshan Bing, Xiangtong Yao, Kejia Chen, Kai Huang, Yang Gao, Fuchun Sun, and Alois Knoll · 2025
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Pleas-merging models with permutations and least squares
Anshul Nasery, Jonathan Hayase, Pang Wei Koh, and Sewoong Oh · 2025
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Gr00t n1: An open foundation model for generalist humanoid robots, 2025
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Fast: Efficient action tokenization for vision-language-action models
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Embodiedonevision: Interleaved vision-text-action pretraining for general robot control, 2025
Delin Qu, Haoming Song, Qizhi Chen, Zhaoqing Chen, Xianqiang Gao, Xinyi Ye, Qi Lv, Modi Shi, Guanghui Ren, Cheng Ruan, Maoqing Yao, Haoran Yang, Jiacheng Bao, Bin Zhao, and Dong Wang · 2025
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Ricl: Adding in-context adaptability to pre-trained vision-language-action models
Kaustubh Sridhar, Souradeep Dutta, Dinesh Jayaraman, and Insup Lee · 2025
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Gemini robotics: Bringing ai into the physical world
Gemini Robotics Team, Saminda Abeyruwan, Joshua Ainslie, Jean-Baptiste Alayrac, Montserrat Gonzalez Arenas, Travis Armstrong, Ashwin Balakrishna, Robert Baruch, Maria Bauza, Michiel Blokzijl, et al · 2025
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Generalization capability for imitation learning
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Parallels between vla model post-training and human motor learning: Progress, challenges, and trends
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Effective tuning strategies for generalist robot manipulation policies
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Efficient continual adaptation of pretrained robotic policy with online meta-learned adapters
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