Urmăriți
Daniel M. Ziegler
Daniel M. Ziegler
Redwood Research
Adresă de e-mail confirmată pe rdwrs.com - Pagina de pornire
Titlu
Citat de
Citat de
Anul
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
396092020
Learning to summarize with human feedback
N Stiennon, L Ouyang, J Wu, D Ziegler, R Lowe, C Voss, A Radford, ...
Advances in Neural Information Processing Systems 33, 3008-3021, 2020
18432020
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
15142019
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
3762020
Using Crash Hoare logic for certifying the FSCQ file system
H Chen, D Ziegler, T Chajed, A Chlipala, MF Kaashoek, N Zeldovich
Proceedings of the 25th Symposium on Operating Systems Principles, 18-37, 2015
3402015
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
2602005
Recursively summarizing books with human feedback
J Wu, L Ouyang, DM Ziegler, N Stiennon, R Lowe, J Leike, P Christiano
arXiv preprint arXiv:2109.10862, 2021
2592021
& Amodei, D.(2020)
TB Brown, B Mann, N Ryder, M Subbiah, J Kaplan, P Dhariwal, ...
Language models are few-shot learners, 2005
2002005
Language models are few-shot learners
B Mann, N Ryder, M Subbiah, J Kaplan, P Dhariwal, A Neelakantan, ...
arXiv preprint arXiv:2005.14165 1, 2020
1932020
Language models are few-shot learners (arXiv: 2005.14165). arXiv
TB Brown, B Mann, N Ryder, M Subbiah, J Kaplan, P Dhariwal, ...
1312005
Sleeper agents: Training deceptive llms that persist through safety training
E Hubinger, C Denison, J Mu, M Lambert, M Tong, M MacDiarmid, ...
arXiv preprint arXiv:2401.05566, 2024
682024
Language models are few-shot learners. cite
TB Brown, B Mann, N Ryder, M Subbiah, J Kaplan, P Dhariwal, ...
arXiv preprint arxiv:2005.14165, 2020
632020
Adversarial training for high-stakes reliability
D Ziegler, S Nix, L Chan, T Bauman, P Schmidt-Nielsen, T Lin, A Scherlis, ...
Advances in Neural Information Processing Systems 35, 9274-9286, 2022
532022
Fine-tuning language models from human preferences (2020)
DM Ziegler, N Stiennon, J Wu, TB Brown, A Radford, D Amodei, ...
URL: http://arxiv. org/abs/1909.08593, 1909
521909
Fine-tuning language models from human preferences. arXiv 2019
DM Ziegler, N Stiennon, J Wu, TB Brown, A Radford, D Amodei, ...
arXiv preprint arXiv:1909.08593, 1909
481909
Language Models are Few-Shot Learners [arXiv: 2005.14165]
TB Brown, B Mann, N Ryder, M Subbiah, J Kaplan, P Dhariwal, ...
arXiv preprint arXiv:2005.14165, 2020
352020
Specifying crash safety for storage systems
H Chen, D Ziegler, A Chlipala, MF Kaashoek, E Kohler, N Zeldovich
15th Workshop on Hot Topics in Operating Systems (HotOS XV), 2015
262015
Learning to summarize from human feedback, 2020
N Stiennon, L Ouyang, J Wu, DM Ziegler, R Lowe, C Voss, A Radford, ...
URL https://arxiv. org/abs, 2009
242009
Certifying a file system using crash hoare logic: correctness in the presence of crashes
T Chajed, H Chen, A Chlipala, MF Kaashoek, N Zeldovich, D Ziegler
Communications of the ACM 60 (4), 75-84, 2017
182017
Recursively summarizing books with human feedback, 2021
J Wu, L Ouyang, DM Ziegler, N Stiennon, R Lowe, J Leike, P Christiano
URL https://arxiv. org/abs/2109.10862, 0
10
Sistemul nu poate realiza operația în acest moment. Încercați din nou mai târziu.
Articole 1–20