Publications
Journals
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OpenAI: M. Andrychowicz, B. Baker, M. Chociej, R. Jozefowicz, B.
McGrew, J. Pachocki, A. Petron, M. Plappert, G.
Powell, A. Ray, J. Schneider, S. Sidor, J. Tobin, P. Welinder, L.
Weng, and W. Zaremba,
Learning Dexterous In-Hand Manipulation,
The International Journal of Robotics Research (IJRR), Vol.
39(1), pp. 3-20, January 2020 (pre-print August 2018) [pdf, pre-print,
blog post,
video 1,
video 2,
bib]
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M. Plappert, C. Mandery, and T. Asfour,
Learning a bidirectional mapping between human whole-body motion
and natural language using deep recurrent neural networks, Robotics and Autonomous Systems, Vol. 109, pp. 13-26,
November 2018 [pdf, video,
dataset,
code,
bib]
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M. Plappert, C. Mandery, and T. Asfour,
The KIT Motion-Language Dataset, Big Data, Vol. 4, No. 4, pp. 236-252, December 2016 [pdf,
dataset,
code, bib]
Conferences
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M. Plappert, R. Houthooft, P. Dhariwal, S. Sidor,
R.Y. Chen, X. Chen, T. Asfour, P. Abbeel, and M. Andrychowicz,
Parameter Space Noise for Exploration,
In the proceedings of the International Conference on Learning
Representations (ICLR), Vancouver, Canada, April 2018 [pdf,
blog post, code,
bib]
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C. Mandery, M. Plappert, J. Borràs, and T. Asfour,
Dimensionality Reduction for Whole-Body Human Motion
Recognition,
19th International Conference on Information Fusion (FUSION), pp.
355-362, July 2016 [pdf, bib]
Pre-Prints & Tech Reports
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K. Cobbe, V. Kosaraju, M. Bavarian, M. Chen, H. Jun, L. Kaiser,
M. Plappert, J. Tworek, J. Hilton, R. Nakano, C.
Hesse, and J. Schulman,
Training Verifiers to Solve Math Word Problems, arXiv:2110.14168, October 2021, [pdf,
blog post]
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M. Chen, J. Tworek, H. Jun, Q. Yuan, H. Ponde de Oliveira Pinto, J.
Kaplan, H. Edwards, Y. Burda, N. Joseph, G. Brockman, A. Ray, R.
Puri, G. Krueger, M. Petrov, H. Khlaaf, G. Sastry, P. Mishkin, B.
Chan, S. Gray, N. Ryder, M. Pavlov, A. Power, L. Kaiser, M.
Bavarian, C. Winter, P. Tillet, F. Such, D. Cummings,
M. Plappert, F. Chantzis, E. Barnes, A.
Herbert-Voss, W.H. Guss, A. Nichol, A. Paino, N. Tezak, J. Tang, I.
Babuschkin, S. Balaji, S. Jain, W. Saunders, C. Hesse, A.N. Carr, J.
Leike, J. Achiam, V. Misra, E. Morikawa, A. Radford, M. Knight, M.
Brundage, M. Murati, K. Mayer, P. Welinder, B. McGrew, D. Amodei, S.
McCandlish, I. Sutskever, and W. Zaremba,
Evaluating Large Language Models Trained on Code, arXiv:2107.03374, July 2021 [pdf, blog post]
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OpenAI: M. Plappert, R. Sampedro, T. Xu, I. Akkaya,
V. Kosaraju, P. Welinder, R. D'Sa, A. Petron, H. Ponde de Oliveira
Pinto, A. Paino, H. Noh, L. Weng, Q. Yuan, C. Chu, and W. Zaremba,
Asymmetric self-play for automatic goal discovery in robotic
manipulation, arXiv:2101.04882, January 2021 [pdf, videos]
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L. Zhang, M. Plappert, and W. Zaremba,
Predicting Sim-to-Real Transfer with Probabilistic Dynamics
Models, arXiv:2009.12864, September 2020 [pdf]
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OpenAI: I. Akkaya, M. Andrychowicz, M. Chociej, M. Litwin, B.
McGrew, A. Petron, A. Paino, M. Plappert, G.
Powell, R. Ribas, J. Schneider, N. Tezak, J. Tworek, P. Welinder, L.
Weng, Q. Yuan, W. Zaremba, and L. Zhang,
Solving Rubik's Cube with a Robot Hand, arXiv:1910.07113, October 2019 [pdf,
blog post,
all videos, bib]
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M. Plappert, M. Andrychowicz, A. Ray, B. McGrew, B.
Baker, G. Powell, J. Schneider, J. Tobin, M. Chociej, P. Welinder,
V. Kumar, and W. Zaremba,
Multi-Goal Reinforcement Learning: Challenging Robotics
Environments and Request for Research, arXiv:1802.09464, February 2018 [pdf,
blog post,
code, bib]
Theses
Talks
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Understanding LLMs - An Introduction to Modern Language
Modeling, Knowunity AI Meetup, October 2023, [slides]
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OpenAI Robotics Symposium 2019, April 2019, [video]
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Learning Dexterity, NeurIPS 2018, Deep Reinforcement Learning Workshop,
December 2018 [slides,
poster]
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Learning Dexterity, karlsruhe.ai / Hack & Söhne, September 2018 [slides]
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Parameter Space Noise for Exploration, heidelberg.ai, May 2018 [slides]
Projects
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Keras-RL, a deep
reinforcement learning library for Keras [docs]
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PiBot, a
simple robot platform based on a Raspberry Pi
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Motion Annotation Tool, a web-based tool to collect natural language descriptions of
human whole-body motion [website]
Coverage
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Codex and GitHub Copilot:
-
Asymmetric self-play for automatic goal discovery in robotic
manipulation:
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Solving Rubik's Cube with a Robot Hand:
-
Learning Dexterous In-Hand Manipulation:
-
Ingredients for Robotics Research:
