| Evaluating large language models trained on code M Chen, J Tworek, H Jun, Q Yuan, HPO Pinto, J Kaplan, H Edwards, ... arXiv preprint arXiv:2107.03374, 2021 | 1950 | 2021 |
| Training verifiers to solve math word problems K Cobbe, V Kosaraju, M Bavarian, M Chen, H Jun, L Kaiser, M Plappert, ... arXiv preprint arXiv:2110.14168, 2021 | 1059 | 2021 |
| Solving rubik's cube with a robot hand I Akkaya, M Andrychowicz, M Chociej, M Litwin, B McGrew, A Petron, ... arXiv preprint arXiv:1910.07113, 2019 | 1045 | 2019 |
| Gpt-4 technical report J Achiam, S Adler, S Agarwal, L Ahmad, I Akkaya, FL Aleman, D Almeida, ... arXiv preprint arXiv:2303.08774, 2023 | 719 | 2023 |
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| Text and code embeddings by contrastive pre-training A Neelakantan, T Xu, R Puri, A Radford, JM Han, J Tworek, Q Yuan, ... arXiv preprint arXiv:2201.10005, 2022 | 221 | 2022 |
| Efficient training of language models to fill in the middle M Bavarian, H Jun, N Tezak, J Schulman, C McLeavey, J Tworek, M Chen arXiv preprint arXiv:2207.14255, 2022 | 83 | 2022 |
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| Systems and methods for generating natural language using language models trained on computer code M Chen, J Tworek, I Sutskever, W Zaremba, JUN Heewoo, HPDEO PINTO US Patent App. 18/321,921, 2024 | | 2024 |
| Systems and methods for generating code using language models trained on computer code M Chen, J Tworek, I Sutskever, W Zaremba, JUN Heewoo, HPDEO PINTO US Patent App. 18/321,852, 2024 | | 2024 |
