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This work presents Mamba Imitation Learning (MaIL), a novel imitation learning (IL) architecture that provides an alternative to state-of-the-art (SoTA) Transformer-based policies.
Learning internal representations by error propagation, parallel distributed processing, explorations in the microstructure of cognition, ed. de rumelhart and j. mcclelland. vol. 1. 1986
D. E. Rumelhart, G. E. Hinton, and R. J. Williams · 1986
Earlier work this paper cites.
Alvinn: An autonomous land vehicle in a neural network
D. A. Pomerleau · 1988
Earlier work this paper cites.
Learning from demonstration
S. Schaal · 1996
Earlier work this paper cites.
Long short-term memory
S. Hochreiter and J. Schmidhuber · 1997
Earlier work this paper cites.
Visualizing data using t-sne
L. Van der Maaten and G. Hinton · 2008
Earlier work this paper cites.
Learning phrase representations using rnn encoder-decoder for statistical machine translation
K. Cho, B. Van Merriënboer, C. Gulcehre, D. Bahdanau, F. Bougares, H. Schwenk, and Y. Bengio · 2014
Earlier work this paper cites.
Empirical evaluation of gated recurrent neural networks on sequence modeling
J. Chung, C. Gulcehre, K. Cho, and Y. Bengio · 2014
Earlier work this paper cites.
Attention is all you need
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, and I. Polosukhin · 2017
Earlier work this paper cites.
Deeply aggrevated: Differentiable imitation learning for sequential prediction
W. Sun, A. Venkatraman, G. J. Gordon, B. Boots, and J. A. Bagnell · 2017
Earlier work this paper cites.
An algorithmic perspective on imitation learning
T. Osa, J. Pajarinen, G. Neumann, J. A. Bagnell, P. Abbeel, J. Peters, et al · 2018
Earlier work this paper cites.
Bert: Pre-training of deep bidirectional transformers for language understanding, 2019
J. Devlin, M.-W. Chang, K. Lee, and K. Toutanova · 2019
Earlier work this paper cites.
Imitation learning for human pose prediction
B. Wang, E. Adeli, H.-k. Chiu, D.-A. Huang, and J. C. Niebles · 2019
Earlier work this paper cites.
Learning latent plans from play
C. Lynch, M. Khansari, T. Xiao, V. Kumar, J. Tompson, S. Levine, and P. Sermanet · 2020
Earlier work this paper cites.
Denoising diffusion probabilistic models
J. Ho, A. Jain, and P. Abbeel · 2020
Earlier work this paper cites.
What matters in learning from offline human demonstrations for robot manipulation
A. Mandlekar, D. Xu, J. Wong, S. Nasiriany, C. Wang, R. Kulkarni, L. Fei-Fei, S. Savarese, Y. Zhu, and R. Martín-Martín · 2021
Earlier work this paper cites.
An image is worth 16x16 words: Transformers for image recognition at scale
A. Dosovitskiy, L. Beyer, A. Kolesnikov, D. Weissenborn, X. Zhai, T. Unterthiner, M. Dehghani, M. Minderer, G. Heigold, S. Gelly, J. Uszkoreit, and N. Houlsby · 2021
Earlier work this paper cites.
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C. Du, Z. Wang, A. A. Malcolm, and C. L. Ho · 2021
Cited alongside, same era.
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A. Radford, J. W. Kim, C. Hallacy, A. Ramesh, G. Goh, S. Agarwal, G. Sastry, A. Askell, P. Mishkin, J. Clark, et al · 2021
Cited alongside, same era.
Polymetis
Y. Lin, A. S. Wang, G. Sutanto, A. Rai, and F. Meier · 2021
Cited alongside, same era.
Implicit behavioral cloning
P. Florence, C. Lynch, A. Zeng, O. A. Ramirez, A. Wahid, L. Downs, A. Wong, J. Lee, I. Mordatch, and J. Tompson · 2022
Cited alongside, same era.
Diagonal state spaces are as effective as structured state spaces
A. Gupta, A. Gu, and J. Berant · 2022
J. Achiam, S. Adler, S. Agarwal, L. Ahmad, I. Akkaya, F. L. Aleman, D. Almeida, J. Altenschmidt, S. Altman, S. Anadkat, et al · 2023
Later among the works it cites.
Simplified state space layers for sequence modeling
J. T. Smith, A. Warrington, and S. Linderman · 2023
Later among the works it cites.
Perceiver-actor: A multi-task transformer for robotic manipulation
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Later among the works it cites.
Unleashing large-scale video generative pre-training for visual robot manipulation
H. Wu, Y. Jing, C. Cheang, G. Chen, J. Xu, X. Li, M. Liu, H. Li, and T. Kong · 2023
Later among the works it cites.
Mutex: Learning unified policies from multimodal task specifications
R. Shah, R. Martín-Martín, and Y. Zhu · 2023
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Cited alongside, same era.
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Nomad: Goal masked diffusion policies for navigation and exploration
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Effectively modeling time series with simple discrete state spaces, 2023
M. Zhang, K. K. Saab, M. Poli, T. Dao, K. Goel, and C. Ré · 2023
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