Language models are few-shot learners TB Brown arXiv preprint ArXiv:2005.14165, 2020 | 30541 | 2020 |
Hierarchical text-conditional image generation with clip latents A Ramesh, P Dhariwal, A Nichol, C Chu, M Chen arXiv preprint arXiv:2204.06125 1 (2), 3, 2022 | 5257 | 2022 |
Zero-shot text-to-image generation A Ramesh, M Pavlov, G Goh, S Gray, C Voss, A Radford, M Chen, ... International conference on machine learning, 8821-8831, 2021 | 4300 | 2021 |
Gpt-4 technical report J Achiam, S Adler, S Agarwal, L Ahmad, I Akkaya, FL Aleman, D Almeida, ... arXiv preprint arXiv:2303.08774, 2023 | 2963 | 2023 |
Evaluating large language models trained on code M Chen, J Tworek, H Jun, Q Yuan, HPDO Pinto, J Kaplan, H Edwards, ... arXiv preprint arXiv:2107.03374, 2021 | 2825* | 2021 |
Glide: Towards photorealistic image generation and editing with text-guided diffusion models A Nichol, P Dhariwal, A Ramesh, P Shyam, P Mishkin, B McGrew, ... arXiv preprint arXiv:2112.10741, 2021 | 2618 | 2021 |
Generative pretraining from pixels M Chen, A Radford, R Child, J Wu, H Jun, D Luan, I Sutskever International conference on machine learning, 1691-1703, 2020 | 1621 | 2020 |
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 | 1542 | 2021 |
Consistency models Y Song, P Dhariwal, M Chen, I Sutskever arXiv preprint arXiv:2303.01469, 2023 | 471 | 2023 |
Point-e: A system for generating 3d point clouds from complex prompts A Nichol, H Jun, P Dhariwal, P Mishkin, M Chen arXiv preprint arXiv:2212.08751, 2022 | 371 | 2022 |
Scaling laws for autoregressive generative modeling T Henighan, J Kaplan, M Katz, M Chen, C Hesse, J Jackson, H Jun, ... arXiv preprint arXiv:2010.14701, 2020 | 297 | 2020 |
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 | 103 | 2022 |
DALL· E: Creating images from text A Ramesh, M Pavlov, G Goh, S Gray, M Chen, R Child, V Misra, P Mishkin, ... OpenAI blog 2, 2021 | 90 | 2021 |
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Distribution augmentation for generative modeling H Jun, R Child, M Chen, J Schulman, A Ramesh, A Radford, I Sutskever International Conference on Machine Learning, 5006-5019, 2020 | 58 | 2020 |
Using Temporal Correlations and Full Distributions to Separate Intrinsic<? format?> and Extrinsic Fluctuations in Biological Systems A Hilfinger, M Chen, J Paulsson Physical review letters 109 (24), 248104, 2012 | 21 | 2012 |
Systems and methods for generating natural language using language models trained on computer code M Chen, J Tworek, I Sutskever, W Zaremba, HW Jun, HPDEO PINTO US Patent 12,008,341, 2024 | | 2024 |
Systems and methods for hierarchical text-conditional image generation A Ramesh, P Dhariwal, A Nichol, C Chu, M Chen US Patent 11,922,550, 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 |