Language models are few-shot learners TB Brown arXiv preprint arXiv:2005.14165, 2020 | 36806 | 2020 |
Language models are unsupervised multitask learners A Radford, J Wu, R Child, D Luan, D Amodei, I Sutskever OpenAI blog 1 (8), 9, 2019 | 25056* | 2019 |
Training language models to follow instructions with human feedback L Ouyang, J Wu, X Jiang, D Almeida, C Wainwright, P Mishkin, C Zhang, ... Advances in neural information processing systems 35, 27730-27744, 2022 | 10810 | 2022 |
Gpt-4 technical report J Achiam, S Adler, S Agarwal, L Ahmad, I Akkaya, FL Aleman, D Almeida, ... arXiv preprint arXiv:2303.08774, 2023 | 7303* | 2023 |
Scaling laws for neural language models J Kaplan, S McCandlish, T Henighan, TB Brown, B Chess, R Child, ... arXiv preprint arXiv:2001.08361, 2020 | 2492 | 2020 |
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 | 1777 | 2020 |
Learning to summarize with human feedback N Stiennon, L Ouyang, J Wu, D Ziegler, R Lowe, C Voss, A Radford, ... Advances in Neural Information Processing Systems 33, 3008-3021, 2020 | 1732 | 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 | 1394 | 2019 |
Webgpt: Browser-assisted question-answering with human feedback R Nakano, J Hilton, S Balaji, J Wu, L Ouyang, C Kim, C Hesse, S Jain, ... arXiv preprint arXiv:2112.09332, 2021 | 1090 | 2021 |
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 | 609 | 2019 |
Open x-embodiment: Robotic learning datasets and rt-x models A O'Neill, A Rehman, A Gupta, A Maddukuri, A Gupta, A Padalkar, A Lee, ... arXiv preprint arXiv:2310.08864, 2023 | 352* | 2023 |
Recursively summarizing books with human feedback J Wu, L Ouyang, DM Ziegler, N Stiennon, R Lowe, J Leike, P Christiano arXiv preprint arXiv:2109.10862, 2021 | 255 | 2021 |
Language models can explain neurons in language models S Bills, N Cammarata, D Mossing, H Tillman, L Gao, G Goh, I Sutskever, ... URL https://openaipublic. blob. core. windows. net/neuron-explainer/paper …, 2023 | 209 | 2023 |
Self-critiquing models for assisting human evaluators W Saunders, C Yeh, J Wu, S Bills, L Ouyang, J Ward, J Leike arXiv preprint arXiv:2206.05802, 2022 | 207 | 2022 |
Weak-to-strong generalization: Eliciting strong capabilities with weak supervision C Burns, P Izmailov, JH Kirchner, B Baker, L Gao, L Aschenbrenner, ... arXiv preprint arXiv:2312.09390, 2023 | 170 | 2023 |
Language models are few-shot learners. cite TB Brown, B Mann, N Ryder, M Subbiah, J Kaplan, P Dhariwal, ... arXiv preprint arxiv:2005.14165, 2020 | 53 | 2020 |
Scaling and evaluating sparse autoencoders L Gao, TD la Tour, H Tillman, G Goh, R Troll, A Radford, I Sutskever, ... arXiv preprint arXiv:2406.04093, 2024 | 48 | 2024 |
Fmb: a functional manipulation benchmark for generalizable robotic learning J Luo, C Xu, F Liu, L Tan, Z Lin, J Wu, P Abbeel, S Levine The International Journal of Robotics Research, 02783649241276017, 2023 | 21 | 2023 |
Action-quantized offline reinforcement learning for robotic skill learning J Luo, P Dong, J Wu, A Kumar, X Geng, S Levine Conference on Robot Learning, 1348-1361, 2023 | 17 | 2023 |
Sufficient statistics for team decision problems J Wu Stanford University, 2013 | 11 | 2013 |