Curtis Hawthorne, Andrew Jaegle, Catalina Cangea, Sebastian Borgeaud, Charlie Nash, Mateusz Malinowski, Sander Dieleman, Oriol Vinyals, Matthew M. Botvinick, Ian Simon, Hannah Sheahan, Neil Zeghidour, Jean-Baptiste Alayrac, João Carreira, Jesse H. Engel. General-purpose, long-context autoregressive modeling with Perceiver AR. In Kamalika Chaudhuri, Stefanie Jegelka, Le Song, Csaba Szepesvári, Gang Niu 0001, Sivan Sabato, editors, International Conference on Machine Learning, ICML 2022, 17-23 July 2022, Baltimore, Maryland, USA. Volume 162 of Proceedings of Machine Learning Research, pages 8535-8558, PMLR, 2022. [doi]
@inproceedings{HawthorneJCBNMD22,
title = {General-purpose, long-context autoregressive modeling with Perceiver AR},
author = {Curtis Hawthorne and Andrew Jaegle and Catalina Cangea and Sebastian Borgeaud and Charlie Nash and Mateusz Malinowski and Sander Dieleman and Oriol Vinyals and Matthew M. Botvinick and Ian Simon and Hannah Sheahan and Neil Zeghidour and Jean-Baptiste Alayrac and João Carreira and Jesse H. Engel},
year = {2022},
url = {https://proceedings.mlr.press/v162/hawthorne22a.html},
researchr = {https://researchr.org/publication/HawthorneJCBNMD22},
cites = {0},
citedby = {0},
pages = {8535-8558},
booktitle = {International Conference on Machine Learning, ICML 2022, 17-23 July 2022, Baltimore, Maryland, USA},
editor = {Kamalika Chaudhuri and Stefanie Jegelka and Le Song and Csaba Szepesvári and Gang Niu 0001 and Sivan Sabato},
volume = {162},
series = {Proceedings of Machine Learning Research},
publisher = {PMLR},
}