Jacob Steinhardt

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	Vse	Od leta 2019
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indeks h	50	48
indeks i10	84	76

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Dan HendrycksDirector of the Center for AI Safety (advisor for xAI and Scale)Preverjeni e-poštni naslov na berkeley.edu
Dawn SongProfessor of Computer Science, UC BerkeleyPreverjeni e-poštni naslov na cs.berkeley.edu
Steven BasartPhD, University of ChicagoPreverjeni e-poštni naslov na ttic.edu
Percy LiangAssociate Professor of Computer Science, Stanford UniversityPreverjeni e-poštni naslov na cs.stanford.edu
Christopher OlahAnthropicPreverjeni e-poštni naslov na google.com
John SchulmanAnthropicPreverjeni e-poštni naslov na anthropic.com
Dario AmodeiCEO and Co-Founder at AnthropicPreverjeni e-poštni naslov na anthropic.com
Aditi RaghunathanAssistant professor, Carnegie Mellon UniversityPreverjeni e-poštni naslov na cmu.edu
Paul ChristianoNational Institute of Standards and TechnologyPreverjeni e-poštni naslov na nist.gov
Gregory ValiantAssistant Professor of Computer Science, Stanford UniversityPreverjeni e-poštni naslov na stanford.edu
Pang Wei KohUniversity of WashingtonPreverjeni e-poštni naslov na cs.washington.edu
Zachary C. LiptonRaj Reddy Associate Professor of Machine Learning @ Carnegie Mellon University; CTO + CSO @ AbridgePreverjeni e-poštni naslov na cmu.edu
Moses CharikarProfessor of Computer Science, Stanford UniversityPreverjeni e-poštni naslov na cs.stanford.edu
Jerry LiUniversity of WashingtonPreverjeni e-poštni naslov na cs.washington.edu
Daniel KangUIUCPreverjeni e-poštni naslov na illinois.edu
Tom B BrownAnthropicPreverjeni e-poštni naslov na anthropic.com
Andrew IlyasMassachusetts Institute of TechnologyPreverjeni e-poštni naslov na mit.edu
Pravesh K. KothariPrinceton UniversityPreverjeni e-poštni naslov na cs.cmu.edu
Banghua ZhuUniversity of California, BerkeleyPreverjeni e-poštni naslov na berkeley.edu
Jiantao JiaoAssistant Professor of EECS and Statistics, University of California, BerkeleyPreverjeni e-poštni naslov na berkeley.edu

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Jacob Steinhardt

Stanford University

Preverjeni e-poštni naslov na cs.stanford.edu - Domača stran

Machine learning Statistics


Naslov Razvrsti po navedbah Razvrsti po letniku Razvrsti po naslovu	Navedeno Navedeno	Leto
Concrete problems in AI safety D Amodei, C Olah, J Steinhardt, P Christiano, J Schulman, D Mané arXiv preprint arXiv:1606.06565, 2016	3000	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	2543	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	1669	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	1511	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	1142	2018
Certified defenses against adversarial examples A Raghunathan, J Steinhardt, P Liang arXiv preprint arXiv:1801.09344, 2018	1135	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	1048	2021
Certified defenses for data poisoning attacks J Steinhardt, PWW Koh, PS Liang Advances in neural information processing systems 30, 2017	909	2017
Jailbroken: How does llm safety training fail? A Wei, N Haghtalab, J Steinhardt Advances in Neural Information Processing Systems 36, 2024	637	2024
Semidefinite relaxations for certifying robustness to adversarial examples A Raghunathan, J Steinhardt, PS Liang Advances in neural information processing systems 31, 2018	507	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	488	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	442	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	436	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	341	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	336	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	289	2023

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