| Unsupervised representation learning with deep convolutional generative adversarial networks A Radford, L Metz, S Chintala arXiv preprint arXiv:1511.06434, 2015 | 8374 | 2015 |
| Improved techniques for training gans T Salimans, I Goodfellow, W Zaremba, V Cheung, A Radford, X Chen arXiv preprint arXiv:1606.03498, 2016 | 4556 | 2016 |
| Proximal policy optimization algorithms J Schulman, F Wolski, P Dhariwal, A Radford, O Klimov arXiv preprint arXiv:1707.06347, 2017 | 3573 | 2017 |
| Language Models are Unsupervised Multitask Learners A Radford, J Wu, R Child, D Luan, D Amodei, I Sutskever Technical report, OpenAi, 2019 | 2559* | 2019 |
| Improving language understanding by generative pre-training A Radford, K Narasimhan, T Salimans, I Sutskever | 1997* | 2018 |
| Openai baselines P Dhariwal, C Hesse, O Klimov, A Nichol, M Plappert, A Radford, ... | 593 | 2017 |
| Language models are few-shot learners TB Brown, B Mann, N Ryder, M Subbiah, J Kaplan, P Dhariwal, ... arXiv preprint arXiv:2005.14165, 2020 | 476 | 2020 |
| Learning to generate reviews and discovering sentiment A Radford, R Jozefowicz, I Sutskever arXiv preprint arXiv:1704.01444, 2017 | 312 | 2017 |
| Stable baselines A Hill, A Raffin, M Ernestus, A Gleave, A Kanervisto, R Traore, P Dhariwal, ... | 263 | 2018 |
| Generating long sequences with sparse transformers R Child, S Gray, A Radford, I Sutskever arXiv preprint arXiv:1904.10509, 2019 | 193 | 2019 |
| Improving GANs using optimal transport T Salimans, H Zhang, A Radford, D Metaxas arXiv preprint arXiv:1803.05573, 2018 | 140 | 2018 |
| Proximal policy optimization algorithms (2017) J Schulman, F Wolski, P Dhariwal, A Radford, O Klimov arXiv preprint arXiv:1707.06347, 2017 | 72 | 2017 |
| Gpu kernels for block-sparse weights S Gray, A Radford, DP Kingma arXiv preprint arXiv:1711.09224 3, 2017 | 70 | 2017 |
| Better language models and their implications A Radford, J Wu, D Amodei, D Amodei, J Clark, M Brundage, I Sutskever OpenAI Blog https://openai. com/blog/better-language-models, 2019 | 64 | 2019 |
| Proximal policy optimization algorithms. arXiv 2017 J Schulman, F Wolski, P Dhariwal, A Radford, O Klimov arXiv preprint arXiv:1707.06347, 2017 | 54 | 2017 |
| Release strategies and the social impacts of language models I Solaiman, M Brundage, J Clark, A Askell, A Herbert-Voss, J Wu, ... arXiv preprint arXiv:1908.09203, 2019 | 48 | 2019 |
| Jukebox: A generative model for music P Dhariwal, H Jun, C Payne, JW Kim, A Radford, I Sutskever arXiv preprint arXiv:2005.00341, 2020 | 38 | 2020 |
| Scaling laws for neural language models J Kaplan, S McCandlish, T Henighan, TB Brown, B Chess, R Child, ... arXiv preprint arXiv:2001.08361, 2020 | 32 | 2020 |
| Fine-tuning language models from human preferences DM Ziegler, N Stiennon, J Wu, TB Brown, A Radford, D Amodei, ... arXiv preprint arXiv:1909.08593, 2019 | 32 | 2019 |
| 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 | 15 | 2020 |
Ilya SutskeverCo-Founder and Chief Scientist of OpenAIVerified email at openai.com
