Author of the publication

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Improving Language Models by Retrieving from Trillions of Tokens.

S. Borgeaud, A. Mensch, J. Hoffmann, T. Cai, E. Rutherford, K. Millican, G. van den Driessche, J. Lespiau, B. Damoc, A. Clark, D. de Las Casas, A. Guy, J. Menick, R. Ring, T. Hennigan, S. Huang, L. Maggiore, C. Jones, A. Cassirer, A. Brock, M. Paganini, G. Irving, O. Vinyals, S. Osindero, K. Simonyan, J. Rae, E. Elsen, and L. Sifre. ICML, volume 162 of Proceedings of Machine Learning Research, page 2206-2240. PMLR, (2022)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Eric Hennigan

Marieta Ioana Toma

Zentrosomenmorphologie in Prostatakarzinomen: eine immunhistologische Studie mit Korrelation zu DNA-Ploidie und kliniko-pathologischen ParameternM. Toma. TU Dresden, (2008)

Tom Ring

Tom Garven

Tom Butters

Other publications of authors with the same name

An empirical analysis of compute-optimal large language model training.J. Hoffmann, S. Borgeaud, A. Mensch, E. Buchatskaya, T. Cai, E. Rutherford, D. de Las Casas, L. Hendricks, J. Welbl, A. Clark and 12 other author(s). NeurIPS, (2022)Unified Scaling Laws for Routed Language Models.A. Clark, D. de Las Casas, A. Guy, A. Mensch, M. Paganini, J. Hoffmann, B. Damoc, B. Hechtman, T. Cai, S. Borgeaud and 16 other author(s). ICML, volume 162 of Proceedings of Machine Learning Research, page 4057-4086. PMLR, (2022)Improving language models by retrieving from trillions of tokensS. Borgeaud, A. Mensch, J. Hoffmann, T. Cai, E. Rutherford, K. Millican, G. Driessche, J. Lespiau, B. Damoc, A. Clark and 18 other author(s). (2021)cite arxiv:2112.04426Comment: Fix incorrect reported numbers in Table 14.Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context.M. Reid, N. Savinov, D. Teplyashin, D. Lepikhin, T. Lillicrap, J. Alayrac, R. Soricut, A. Lazaridou, O. Firat, J. Schrittwieser and 43 other author(s). CoRR, (2024)Improving Language Models by Retrieving from Trillions of Tokens.S. Borgeaud, A. Mensch, J. Hoffmann, T. Cai, E. Rutherford, K. Millican, G. van den Driessche, J. Lespiau, B. Damoc, A. Clark and 18 other author(s). ICML, volume 162 of Proceedings of Machine Learning Research, page 2206-2240. PMLR, (2022)Training Compute-Optimal Large Language ModelsJ. Hoffmann, S. Borgeaud, A. Mensch, E. Buchatskaya, T. Cai, E. Rutherford, D. de Las Casas, L. Hendricks, J. Welbl, A. Clark and 12 other author(s). (2022)

BibSonomy

Disambiguation of "Hennigan, Tom"

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Improving Language Models by Retrieving from Trillions of Tokens.

Please choose a person to relate this publication to

Eric Hennigan

Marieta Ioana Toma

Tom Ring

Tom Garven

Tom Butters

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Hennigan, Tom"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Improving Language Models by Retrieving from Trillions of Tokens.

Please choose a person to relate this publication to

Eric Hennigan

Marieta Ioana Toma

Tom Ring

Tom Garven

Tom Butters

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Improving Language Models by Retrieving from Trillions of Tokens.