| Deep reinforcement learning: A brief survey K Arulkumaran, MP Deisenroth, M Brundage, AA Bharath IEEE Signal Processing Magazine 34 (6), 26-38, 2017 | 4195* | 2017 |
| Gpt-4 technical report J Achiam, S Adler, S Agarwal, L Ahmad, I Akkaya, FL Aleman, D Almeida, ... arXiv preprint arXiv:2303.08774, 2023 | 2948* | 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 | 2356 | 2021 |
| The malicious use of artificial intelligence: Forecasting, prevention, and mitigation M Brundage, S Avin, J Clark, H Toner, P Eckersley, B Garfinkel, A Dafoe, ... arXiv preprint arXiv:1802.07228, 2018 | 1074 | 2018 |
| 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 | 443 | 2019 |
| Toward trustworthy AI development: mechanisms for supporting verifiable claims M Brundage, S Avin, J Wang, H Belfield, G Krueger, G Hadfield, H Khlaaf, ... arXiv preprint arXiv:2004.07213, 2020 | 348 | 2020 |
| Better language models and their implications A Radford, J Wu, D Amodei, D Amodei, J Clark, M Brundage, I Sutskever OpenAI blog 1 (2), 2019 | 265 | 2019 |
| Understanding the capabilities, limitations, and societal impact of large language models A Tamkin, M Brundage, J Clark, D Ganguli arXiv preprint arXiv:2102.02503, 2021 | 250 | 2021 |
| All the news that’s fit to fabricate: AI-generated text as a tool of media misinformation S Kreps, RM McCain, M Brundage Journal of experimental political science 9 (1), 104-117, 2022 | 227 | 2022 |
| Limitations and risks of machine ethics M Brundage Journal of Experimental & Theoretical Artificial Intelligence 26 (3), 355-372, 2014 | 150 | 2014 |
| Evaluating clip: towards characterization of broader capabilities and downstream implications S Agarwal, G Krueger, J Clark, A Radford, JW Kim, M Brundage arXiv preprint arXiv:2108.02818, 2021 | 103 | 2021 |
| The role of cooperation in responsible AI development A Askell, M Brundage, G Hadfield arXiv preprint arXiv:1907.04534, 2019 | 70 | 2019 |
| Frontier AI regulation: Managing emerging risks to public safety M Anderljung, J Barnhart, J Leung, A Korinek, C O'Keefe, J Whittlestone, ... arXiv preprint arXiv:2307.03718, 2023 | 58 | 2023 |
| Taking superintelligence seriously: Superintelligence: Paths, dangers, strategies by nick bostrom (Oxford university press, 2014) M Brundage Futures 72, 32-35, 2015 | 47 | 2015 |
| Should we fear artificial intelligence?: in-depth analysis PJ Bentley, M Brundage, O Häggström, T Metzinger European Parliament, 2018 | 41 | 2018 |
| Smart policies for artificial intelligence M Brundage, J Bryson arXiv preprint arXiv:1608.08196, 2016 | 40 | 2016 |
| Artificial intelligence and responsible innovation M Brundage Fundamental issues of artificial intelligence, 543-554, 2016 | 38 | 2016 |
| Filling gaps in trustworthy development of AI S Avin, H Belfield, M Brundage, G Krueger, J Wang, A Weller, ... Science 374 (6573), 1327-1329, 2021 | 35 | 2021 |
| Evaluating large language models trained on code. arXiv 2021 M Chen, J Tworek, H Jun, Q Yuan, HPO Pinto, J Kaplan, H Edwards, ... arXiv preprint arXiv:2107.03374 10, 2021 | 35 | 2021 |
| Accounting for the neglected dimensions of ai progress F Martınez-Plumed, S Avin, M Brundage, A Dafoe, SO hÉigeartaigh, ... arXiv preprint arXiv:1806.00610 19, 2018 | 24 | 2018 |
Anil Anthony BharathDept of Bioengineering, Imperial College在 imperial.ac.uk 的电子邮件经过验证
