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Tom B Brown
Tom B Brown
Anthropic
E-mailová adresa ověřena na: anthropic.com - Domovská stránka
Název
Citace
Citace
Rok
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
30075*2020
Deep reinforcement learning from human preferences
PF Christiano, J Leike, T Brown, M Martic, S Legg, D Amodei
Advances in neural information processing systems 30, 2017
20792017
Extracting training data from large language models
N Carlini, F Tramer, E Wallace, M Jagielski, A Herbert-Voss, K Lee, ...
30th USENIX Security Symposium (USENIX Security 21), 2633-2650, 2021
11982021
Scaling laws for neural language models
J Kaplan, S McCandlish, T Henighan, TB Brown, B Chess, R Child, ...
arXiv preprint arXiv:2001.08361, 2020
10952020
Adversarial patch
TB Brown, D Mané, A Roy, M Abadi, J Gilmer
arXiv preprint arXiv:1712.09665, 2017
9262017
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
8522019
Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei. 2020. Scaling laws for neural language models
J Kaplan, S McCandlish, T Henighan, TB Brown, B Chess
arXiv preprint arXiv:2001.08361 2, 1557-1566, 2020
7442020
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
6712022
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
6202020
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
5772022
Technical report on the cleverhans v2. 1.0 adversarial examples library
N Papernot, F Faghri, N Carlini, I Goodfellow, R Feinman, A Kurakin, ...
arXiv preprint arXiv:1610.00768, 2016
531*2016
Aurko Roy, Martın Abadi, and Justin Gilmer. Adversarial patch
TB Brown, D Mané
arXiv preprint arXiv:1712.09665 2 (3), 4, 2017
4852017
cleverhans v2. 0.0: an adversarial machine learning library
N Papernot, I Goodfellow, R Sheatsley, R Feinman, P McDaniel
arXiv preprint arXiv:1610.00768 10, 2016
3192016
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
2312020
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
2202022
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
2112021
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
2102022
In-context learning and induction heads
C Olsson, N Elhage, N Nanda, N Joseph, N DasSarma, T Henighan, ...
arXiv preprint arXiv:2209.11895, 2022
1852022
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
1692022
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
1482021
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Články 1–20