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Rewon Child
Rewon Child
Founding Team / Technical Staff at Inflection
E-mailová adresa ověřena na: inflection.ai - 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
48535*2020
Language models are unsupervised multitask learners
A Radford, J Wu, R Child, D Luan, D Amodei, I Sutskever
OpenAI blog 1 (8), 9, 2019
26410*2019
Palm: Scaling language modeling with pathways
A Chowdhery, S Narang, J Devlin, M Bosma, G Mishra, A Roberts, ...
Journal of Machine Learning Research 24 (240), 1-113, 2023
56042023
Scaling laws for neural language models
J Kaplan, S McCandlish, T Henighan, TB Brown, B Chess, R Child, ...
arXiv preprint arXiv:2001.08361, 2020
27362020
Generating long sequences with sparse transformers
R Child, S Gray, A Radford, I Sutskever
arXiv preprint arXiv:1904.10509, 2019
21152019
Generative pretraining from pixels
M Chen, A Radford, R Child, J Wu, H Jun, D Luan, I Sutskever
International conference on machine learning, 1691-1703, 2020
18772020
Using deepspeed and megatron to train megatron-turing nlg 530b, a large-scale generative language model
S Smith, M Patwary, B Norick, P LeGresley, S Rajbhandari, J Casper, ...
arXiv preprint arXiv:2201.11990, 2022
6862022
Very deep vaes generalize autoregressive models and can outperform them on images
R Child
International Conference on Learning Representations (ICLR) 2021, Spotlight, 2020
3592020
Convolutional recurrent neural networks for small-footprint keyword spotting
SO Arik, M Kliegl, R Child, J Hestness, A Gibiansky, C Fougner, ...
arXiv preprint arXiv:1703.05390, 2017
303*2017
Exploring neural transducers for end-to-end speech recognition
E Battenberg, J Chen, R Child, A Coates, YGY Li, H Liu, S Satheesh, ...
2017 IEEE automatic speech recognition and understanding workshop (ASRU …, 2017
292*2017
& 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
1942020
Scaling laws for neural language models. arXiv 2020
J Kaplan, S McCandlish, T Henighan, TB Brown, B Chess, R Child, ...
arXiv preprint arXiv:2001.08361, 2001
1392001
Language models are few-shot learners (arXiv: 2005.14165). arXiv
TB Brown, B Mann, N Ryder, M Subbiah, J Kaplan, P Dhariwal, ...
1322005
Palm: Scaling language modeling with pathways. arXiv 2022
A Chowdhery, S Narang, J Devlin, M Bosma, G Mishra, A Roberts, ...
arXiv preprint arXiv:2204.02311 10, 2022
1232022
DALL· E: Creating images from text
A Ramesh, M Pavlov, G Goh, S Gray, M Chen, R Child, V Misra, P Mishkin, ...
OpenAI blog 2, 2021
1082021
Scaling laws for neural language models (2020)
J Kaplan, S McCandlish, T Henighan, TB Brown, B Chess, R Child, ...
arXiv preprint arXiv:2001.08361, 2001
842001
Active learning for speech recognition: the power of gradients
J Huang, R Child, V Rao, H Liu, S Satheesh, A Coates
arXiv preprint arXiv:1612.03226, 2016
822016
Language models are few-shot learners
A Radford, J Wu, R Child, D Luan, D Amodei, I Sutskever
Adv. Neural Inf. Process. Syst 33, 146, 2020
752020
Language models are unsupervised multitask learners. OpenAI blog (2019)
A Radford, J Wu, R Child, D Luan, D Amodei, I Sutskever
URL: https://cdn. openai. com/better-language-models …, 2022
732022
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Články 1–20