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Evaluating Large Language Models Trained on Code

M. Chen, J. Tworek, H. Jun, Q. Yuan, H. 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. Guss, A. Nichol, A. Paino, N. Tezak, J. Tang, I. Babuschkin, S. Balaji, S. Jain, W. Saunders, C. Hesse, A. 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. arXiv:cs.LG/2107.03374. arXiv, (2021)

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Herbert Güß

Peter Hebgen

Peter Güß

Andreas Hebgen

Ursula Hebgen

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Towards robust and domain agnostic reinforcement learning competitions: MineRL 2020.W. Guss, S. Milani, N. Topin, B. Houghton, S. Mohanty, A. Melnik, A. Harter, B. Buschmaas, B. Jaster, C. Berganski and 19 other author(s). NeurIPS (Competition and Demos), volume 133 of Proceedings of Machine Learning Research, page 233-252. PMLR, (2020)Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark.S. Mohanty, J. Poonganam, A. Gaidon, A. Kolobov, B. Wulfe, D. Chakraborty, G. Semetulskis, J. Schapke, J. Kubilius, J. Pasukonis and 13 other author(s). CoRR, (2021)Multi-task curriculum learning in a complex, visual, hard-exploration domain: Minecraft.I. Kanitscheider, J. Huizinga, D. Farhi, W. Guss, B. Houghton, R. Sampedro, P. Zhokhov, B. Baker, A. Ecoffet, J. Tang and 2 other author(s). CoRR, (2021)Towards robust and domain agnostic reinforcement learning competitions.W. Guss, S. Milani, N. Topin, B. Houghton, S. Mohanty, A. Melnik, A. Harter, B. Buschmaas, B. Jaster, C. Berganski and 19 other author(s). CoRR, (2021)Evaluating Large Language Models Trained on Code.M. Chen, J. Tworek, H. Jun, Q. Yuan, H. de Oliveira Pinto, J. Kaplan, H. Edwards, Y. Burda, N. Joseph, G. Brockman and 48 other author(s). CoRR, (2021)Measuring Sample Efficiency and Generalization in Reinforcement Learning Benchmarks: NeurIPS 2020 Procgen Benchmark.S. Mohanty, J. Poonganam, A. Gaidon, A. Kolobov, B. Wulfe, D. Chakraborty, G. Semetulskis, J. Schapke, J. Kubilius, J. Pasukonis and 13 other author(s). NeurIPS (Competition and Demos), volume 133 of Proceedings of Machine Learning Research, page 361-395. PMLR, (2020)

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Disambiguation of "Guss, William Hebgen"

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Evaluating Large Language Models Trained on Code

Please choose a person to relate this publication to

Herbert Güß

Peter Hebgen

Peter Güß

Andreas Hebgen

Ursula Hebgen

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Guss, William Hebgen"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Evaluating Large Language Models Trained on Code

Please choose a person to relate this publication to

Herbert Güß

Peter Hebgen

Peter Güß

Andreas Hebgen

Ursula Hebgen

Other publications of authors with the same name

Disambiguation

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URL
DOI
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Evaluating Large Language Models Trained on Code