| Language models are few-shot learners T Brown, B Mann, N Ryder, M Subbiah, JD Kaplan, P Dhariwal, ... Advances in neural information processing systems 33, 1877-1901, 2020 | 22428* | 2020 |
| Proximal policy optimization algorithms J Schulman, F Wolski, P Dhariwal, A Radford, O Klimov arXiv preprint arXiv:1707.06347, 2017 | 14815 | 2017 |
| 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 | 2968 | 2022 |
| Glow: Generative flow with invertible 1x1 convolutions DP Kingma, P Dhariwal Advances in neural information processing systems 31, 2018 | 2815 | 2018 |
| Diffusion models beat gans on image synthesis P Dhariwal, A Nichol Advances in neural information processing systems 34, 8780-8794, 2021 | 2643 | 2021 |
| Improved denoising diffusion probabilistic models AQ Nichol, P Dhariwal International Conference on Machine Learning, 8162-8171, 2021 | 1365 | 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 | 1362 | 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 | 1242 | 2020 |
| Openai baselines P Dhariwal, C Hesse, O Klimov, A Nichol, M Plappert, A Radford, ... | 995 | 2017 |
| Stable baselines A Hill, A Raffin, M Ernestus, A Gleave, A Kanervisto, R Traore, P Dhariwal, ... | 849 | 2018 |
| Variational lossy autoencoder X Chen, DP Kingma, T Salimans, Y Duan, P Dhariwal, J Schulman, ... arXiv preprint arXiv:1611.02731, 2016 | 735 | 2016 |
| Parameter space noise for exploration M Plappert, R Houthooft, P Dhariwal, S Sidor, RY Chen, X Chen, T Asfour, ... arXiv preprint arXiv:1706.01905, 2017 | 678 | 2017 |
| Jukebox: A generative model for music P Dhariwal, H Jun, C Payne, JW Kim, A Radford, I Sutskever arXiv preprint arXiv:2005.00341, 2020 | 551 | 2020 |
| 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 | 187 | 2020 |
| Language models are few shot learners NRMSJ Kaplan, PDANP Shyam, GSAAS Agarwal, AHVGK Tom, ... arXiv preprint arXiv:2005.14165 3, 2020 | 130* | 2020 |
| 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 | 125 | 2022 |
| Consistency models Y Song, P Dhariwal, M Chen, I Sutskever arXiv preprint arXiv:2303.01469, 2023 | 115 | 2023 |
| Gamepad: A learning environment for theorem proving D Huang, P Dhariwal, D Song, I Sutskever arXiv preprint arXiv:1806.00608, 2018 | 94 | 2018 |
| Language models are few-shot learners. CoRR abs/2005.14165 (2020) TB Brown, B Mann, N Ryder, M Subbiah, J Kaplan, P Dhariwal, ... URL: https://arxiv. org/abs/2005.14165, 2005 | 47 | 2005 |
| Improved techniques for training consistency models Y Song, P Dhariwal arXiv preprint arXiv:2310.14189, 2023 | 3 | 2023 |
Alec RadfordOpenAIVerified email at openai.com
