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Predictive manipulation has recently gained considerable attention in the Embodied AI community due to its potential to improve robot policy performance by leveraging predicted states.
Imagination-augmented agents for deep reinforcement learning
S. Racanière, T. Weber, D. Reichert, L. Buesing, A. Guez, D. Jimenez Rezende, A. Puigdomènech Badia, O. Vinyals, N. Heess, Y. Li, et al · 2017
Earlier work this paper cites.
Proximal policy optimization algorithms
J. Schulman, F. Wolski, P. Dhariwal, A. Radford, and O. Klimov · 2017
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D. Ha and J. Schmidhuber · 2018
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Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor
T. Haarnoja, A. Zhou, P. Abbeel, and S. Levine · 2018
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Dream to control: Learning behaviors by latent imagination
D. Hafner, T. P. Lillicrap, J. Ba, and M. Norouzi · 2020
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Mastering atari with discrete world models
D. Hafner, T. P. Lillicrap, M. Norouzi, and J. Ba · 2021
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Cyclip: Cyclic contrastive language-image pretraining
S. Goel, H. Bansal, S. Bhatia, R. Rossi, V. Vinay, and A. Grover · 2022
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Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation
J. Li, D. Li, C. Xiong, and S. Hoi · 2022
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Calvin: A benchmark for language-conditioned policy learning for long-horizon robot manipulation tasks
O. Mees, L. Hermann, E. Rosete-Beas, and W. Burgard · 2022
Earlier work this paper cites.
Transformers are sample-efficient world models
V. Micheli, E. Alonso, and F. Fleuret · 2023
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Sigmoid loss for language image pre-training
X. Zhai, B. Mustafa, A. Kolesnikov, and L. Beyer · 2023
Cited alongside, same era.
Mastering diverse domains through world models
D. Hafner, J. Pasukonis, J. Ba, and T. Lillicrap · 2023
Cited alongside, same era.
Simultaneous image-to-zero and zero-to-noise: Diffusion models with analytical image attenuation
Y. Huang, Z. Qin, X. Liu, and K. Xu · 2023
Cited alongside, same era.
Scalable diffusion models with transformers
W. Peebles and S. Xie · 2023
Cited alongside, same era.
Any-point trajectory modeling for policy learning
C. Wen, X. Lin, J. I. R. So, K. Chen, Q. Dou, Y. Gao, and P. Abbeel · 2024
Cited alongside, same era.
Learning to act from actionless videos through dense correspondences
Dinov2: Learning robust visual features without supervision
M. Oquab, T. Darcet, T. Moutakanni, H. Vo, M. Szafraniec, V. Khalidov, P. Fernandez, D. Haziza, F. Massa, A. El-Nouby, et al · 2024
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Z. Ding, A. Zhang, Y. Tian, and Q. Zheng · 2024
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Diffusion for world modeling: Visual details matter in atari
E. Alonso, A. Jelley, V. Micheli, A. Kanervisto, A. J. Storkey, T. Pearce, and F. Fleuret · 2024
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Libero: Benchmarking knowledge transfer for lifelong robot learning
B. Liu, Y. Zhu, C. Gao, Y. Feng, Q. Liu, Y. Zhu, and P. Stone · 2024
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Open x-embodiment: Robotic learning datasets and rt-x models: Open x-embodiment collaboration 0
A. O’Neill, A. Rehman, A. Maddukuri, A. Gupta, A. Padalkar, A. Lee, A. Pooley, A. Gupta, A. Mandlekar, A. Jain, et al · 2024
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P. Ko, J. Mao, Y. Du, S. Sun, and J. B. Tenenbaum · 2024
Cited alongside, same era.
Learning interactive real-world simulators
S. Yang, Y. Du, S. K. S. Ghasemipour, J. Tompson, L. P. Kaelbling, D. Schuurmans, and P. Abbeel · 2024
Cited alongside, same era.
Dino-wm: World models on pre-trained visual features enable zero-shot planning
G. Zhou, H. Pan, Y. LeCun, and L. Pinto · 2024
Cited alongside, same era.
TD-MPC2: scalable, robust world models for continuous control
N. Hansen, H. Su, and X. Wang · 2024
Cited alongside, same era.
Grounding dino: Marrying dino with grounded pre-training for open-set object detection
S. Liu, Z. Zeng, T. Ren, F. Li, H. Zhang, J. Yang, Q. Jiang, C. Li, J. Yang, H. Su, et al · 2024
Cited alongside, same era.
An on-line algorithm for dynamic reinforcement learning and planning in reactive environments
J. Schmidhuber
Cited in the paper.
Reinforcement learning in markovian and non-markovian environments
J. Schmidhuber
Cited in the paper.
Droid: A large-scale in-the-wild robot manipulation dataset
A. Khazatsky, K. Pertsch, S. Nair, A. Balakrishna, S. Dasari, S. Karamcheti, S. Nasiriany, M. K. Srirama, L. Y. Chen, K. Ellis, et al · 2024
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Automate: Specialist and generalist assembly policies over diverse geometries
B. Tang, I. Akinola, J. Xu, B. Wen, A. Handa, K. V. Wyk, D. Fox, G. S. Sukhatme, F. Ramos, and Y. S. Narang · 2024
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Openvla: An open-source vision-language-action model
M. J. Kim, K. Pertsch, S. Karamcheti, T. Xiao, A. Balakrishna, S. Nair, R. Rafailov, E. P. Foster, P. R. Sanketi, Q. Vuong, T. Kollar, B. Burchfiel, R. Tedrake, D. Sadigh, S. Levine, P. Liang, and C. Finn · 2024
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Predictive inverse dynamics models are scalable learners for robotic manipulation
Y. Tian, S. Yang, J. Zeng, P. Wang, D. Lin, H. Dong, and J. Pang · 2025
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