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Tom Henighan
Tom Henighan
Anthropic
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Year
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
232362020
Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray
TB Brown, B Mann, N Ryder, M Subbiah, J Kaplan, P Dhariwal, ...
Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford …, 2020
63152020
Scaling laws for neural language models
J Kaplan, S McCandlish, T Henighan, TB Brown, B Chess, R Child, ...
arXiv preprint arXiv:2001.08361, 2020
17292020
Training a helpful and harmless assistant with reinforcement learning from human feedback
Y Bai, A Jones, K Ndousse, A Askell, A Chen, N DasSarma, D Drain, ...
arXiv preprint arXiv:2204.05862, 2022
6352022
Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei. Scaling laws for neural language models
J Kaplan, S McCandlish, T Henighan, TB Brown, B Chess
arXiv preprint arXiv:2001.08361 1 (2), 4, 2020
5922020
Constitutional ai: Harmlessness from ai feedback
Y Bai, S Kadavath, S Kundu, A Askell, J Kernion, A Jones, A Chen, ...
arXiv preprint arXiv:2212.08073, 2022
5392022
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
2252020
Ultrafast disordering of vanadium dimers in photoexcited VO2
S Wall, S Yang, L Vidas, M Chollet, JM Glownia, M Kozina, T Katayama, ...
Science 362 (6414), 572-576, 2018
2162018
Language models (mostly) know what they know
S Kadavath, T Conerly, A Askell, T Henighan, D Drain, E Perez, ...
arXiv preprint arXiv:2207.05221, 2022
2132022
A general language assistant as a laboratory for alignment
A Askell, Y Bai, A Chen, D Drain, D Ganguli, T Henighan, A Jones, ...
arXiv preprint arXiv:2112.00861, 2021
2002021
Red teaming language models to reduce harms: Methods, scaling behaviors, and lessons learned
D Ganguli, L Lovitt, J Kernion, A Askell, Y Bai, S Kadavath, B Mann, ...
arXiv preprint arXiv:2209.07858, 2022
1962022
In-context learning and induction heads
C Olsson, N Elhage, N Nanda, N Joseph, N DasSarma, T Henighan, ...
arXiv preprint arXiv:2209.11895, 2022
1742022
Predictability and surprise in large generative models
D Ganguli, D Hernandez, L Lovitt, A Askell, Y Bai, A Chen, T Conerly, ...
Proceedings of the 2022 ACM Conference on Fairness, Accountability, and …, 2022
1612022
A mathematical framework for transformer circuits
N Elhage, N Nanda, C Olsson, T Henighan, N Joseph, B Mann, A Askell, ...
Transformer Circuits Thread 1, 1, 2021
1432021
Language Models are Few-Shot Learners. 2020. doi: 10.48550
TB Brown, B Mann, N Ryder, M Subbiah, J Kaplan, P Dhariwal, ...
arxiv, 5-7, 2005
1402005
Magnetic wire traps and programmable manipulation of biological cells
G Vieira, T Henighan, A Chen, AJ Hauser, FY Yang, JJ Chalmers, ...
Physical review letters 103 (12), 128101, 2009
1382009
Anomalous nonlinear X-ray Compton scattering
M Fuchs, M Trigo, J Chen, S Ghimire, S Shwartz, M Kozina, M Jiang, ...
Nature Physics 11 (11), 964-970, 2015
1352015
Toy models of superposition
N Elhage, T Hume, C Olsson, N Schiefer, T Henighan, S Kravec, ...
arXiv preprint arXiv:2209.10652, 2022
1332022
Highly parallel magnetic tweezers by targeted DNA tethering
I De Vlaminck, T Henighan, MTJ van Loenhout, I Pfeiffer, J Huijts, ...
Nano letters 11 (12), 5489-5493, 2011
1322011
Language models are few-shot learners. arXiv
TB Brown, B Mann, N Ryder, M Subbiah, J Kaplan, P Dhariwal, ...
Computer Science, Computation and Language, 2005
1312005
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