Jacob Steinhardt

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Citations	21734	20839
h-index	50	48
i10-index	84	76

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Dan HendrycksDirector of the Center for AI Safety (advisor for xAI and Scale)Verified email at berkeley.edu
Dawn SongProfessor of Computer Science, UC BerkeleyVerified email at cs.berkeley.edu
Steven BasartPhD, University of ChicagoVerified email at ttic.edu
Percy LiangAssociate Professor of Computer Science, Stanford UniversityVerified email at cs.stanford.edu
Christopher OlahAnthropicVerified email at google.com
John SchulmanAnthropicVerified email at anthropic.com
Dario AmodeiCEO and Co-Founder at AnthropicVerified email at anthropic.com
Aditi RaghunathanAssistant professor, Carnegie Mellon UniversityVerified email at cmu.edu
Paul ChristianoNational Institute of Standards and TechnologyVerified email at nist.gov
Gregory ValiantAssistant Professor of Computer Science, Stanford UniversityVerified email at stanford.edu
Pang Wei KohUniversity of WashingtonVerified email at cs.washington.edu
Zachary C. LiptonRaj Reddy Associate Professor of Machine Learning @ Carnegie Mellon University; CTO + CSO @ AbridgeVerified email at cmu.edu
Moses CharikarProfessor of Computer Science, Stanford UniversityVerified email at cs.stanford.edu
Jerry LiUniversity of WashingtonVerified email at cs.washington.edu
Daniel KangUIUCVerified email at illinois.edu
Tom B BrownAnthropicVerified email at anthropic.com
Andrew IlyasMassachusetts Institute of TechnologyVerified email at mit.edu
Pravesh K. KothariPrinceton UniversityVerified email at cs.cmu.edu
Banghua ZhuUniversity of California, BerkeleyVerified email at berkeley.edu
Jiantao JiaoAssistant Professor of EECS and Statistics, University of California, BerkeleyVerified email at berkeley.edu

Jacob Steinhardt

Stanford University

Verified email at cs.stanford.edu - Homepage

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Concrete problems in AI safety D Amodei, C Olah, J Steinhardt, P Christiano, J Schulman, D Mané arXiv preprint arXiv:1606.06565, 2016	2990	2016
Measuring massive multitask language understanding D Hendrycks, C Burns, S Basart, A Zou, M Mazeika, D Song, J Steinhardt arXiv preprint arXiv:2009.03300, 2020	2503	2020
The many faces of robustness: A critical analysis of out-of-distribution generalization D Hendrycks, S Basart, N Mu, S Kadavath, F Wang, E Dorundo, R Desai, ... Proceedings of the IEEE/CVF international conference on computer vision …, 2021	1650	2021
Natural adversarial examples D Hendrycks, K Zhao, S Basart, J Steinhardt, D Song Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021	1491	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	1134	2018
Certified defenses against adversarial examples A Raghunathan, J Steinhardt, P Liang arXiv preprint arXiv:1801.09344, 2018	1129	2018
Measuring mathematical problem solving with the math dataset D Hendrycks, C Burns, S Kadavath, A Arora, S Basart, E Tang, D Song, ... arXiv preprint arXiv:2103.03874, 2021	1025	2021
Certified defenses for data poisoning attacks J Steinhardt, PWW Koh, PS Liang Advances in neural information processing systems 30, 2017	906	2017
Jailbroken: How does llm safety training fail? A Wei, N Haghtalab, J Steinhardt Advances in Neural Information Processing Systems 36, 2024	622	2024
Semidefinite relaxations for certifying robustness to adversarial examples A Raghunathan, J Steinhardt, PS Liang Advances in neural information processing systems 31, 2018	506	2018
Measuring coding challenge competence with apps D Hendrycks, S Basart, S Kadavath, M Mazeika, A Arora, E Guo, C Burns, ... arXiv preprint arXiv:2105.09938, 2021	482	2021
Scaling out-of-distribution detection for real-world settings D Hendrycks, S Basart, M Mazeika, A Zou, J Kwon, M Mostajabi, ... arXiv preprint arXiv:1911.11132, 2019	432	2019
Aligning ai with shared human values D Hendrycks, C Burns, S Basart, A Critch, J Li, D Song, J Steinhardt arXiv preprint arXiv:2008.02275, 2020	430	2020
Troubling Trends in Machine Learning Scholarship: Some ML papers suffer from flaws that could mislead the public and stymie future research. ZC Lipton, J Steinhardt Queue 17 (1), 45-77, 2019	381	2019
Sonyc: A system for monitoring, analyzing, and mitigating urban noise pollution JP Bello, C Silva, O Nov, RL Dubois, A Arora, J Salamon, C Mydlarz, ... Communications of the ACM 62 (2), 68-77, 2019	341	2019
Learning from untrusted data M Charikar, J Steinhardt, G Valiant Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing …, 2017	339	2017
Sever: A robust meta-algorithm for stochastic optimization I Diakonikolas, G Kamath, D Kane, J Li, J Steinhardt, A Stewart International Conference on Machine Learning, 1596-1606, 2019	337	2019
Interpretability in the wild: a circuit for indirect object identification in gpt-2 small K Wang, A Variengien, A Conmy, B Shlegeris, J Steinhardt arXiv preprint arXiv:2211.00593, 2022	328	2022
Unsolved problems in ml safety D Hendrycks, N Carlini, J Schulman, J Steinhardt arXiv preprint arXiv:2109.13916, 2021	316	2021
Progress measures for grokking via mechanistic interpretability N Nanda, L Chan, T Lieberum, J Smith, J Steinhardt arXiv preprint arXiv:2301.05217, 2023	284	2023

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