Blaise Agüera y Arcas

Publication Activity (10 Years)

Years Active: 2000-2024
Publications (10 Years): 25

Top Topics

Efficient Learning

Question Answering

Top Venues

Publications

Winnie Street, John Oliver Siy, Geoff Keeling, Adrien Baranes, Benjamin Barnett, Michael McKibben, Tatenda Kanyere, Alison Lentz, Blaise Agüera y Arcas, Robin I. M. Dunbar
LLMs achieve adult human performance on higher-order theory of mind tasks. CoRR (2024)
Blaise Agüera y Arcas, Jyrki Alakuijala, James Evans, Ben Laurie, Alexander Mordvintsev, Eyvind Niklasson, Ettore Randazzo, Luca Versari
Computational Life: How Well-formed, Self-replicating Programs Emerge from Simple Interaction. CoRR (2024)
Iason Gabriel, Arianna Manzini, Geoff Keeling, Lisa Anne Hendricks, Verena Rieser, Hasan Iqbal, Nenad Tomasev, Ira Ktena, Zachary Kenton, Mikel Rodriguez, Seliem El-Sayed, Sasha Brown, Canfer Akbulut, Andrew Trask, Edward Hughes, A. Stevie Bergman, Renee Shelby, Nahema Marchal, Conor Griffin, Juan Mateos-Garcia, Laura Weidinger, Winnie Street, Benjamin Lange, Alex Ingerman, Alison Lentz, Reed Enger, Andrew Barakat, Victoria Krakovna, John Oliver Siy, Zeb Kurth-Nelson, Amanda McCroskery, Vijay Bolina, Harry Law, Murray Shanahan, Lize Alberts, Borja Balle, Sarah de Haas, Yetunde Ibitoye, Allan Dafoe, Beth Goldberg, Sébastien Krier, Alexander Reese, Sims Witherspoon, Will Hawkins, Maribeth Rauh, Don Wallace, Matija Franklin, Josh A. Goldstein, Joel Lehman, Michael Klenk, Shannon Vallor, Courtney Biles, Meredith Ringel Morris, Helen King, Blaise Agüera y Arcas, William Isaac, James Manyika
The Ethics of Advanced AI Assistants. CoRR (2024)
Florian Hartmann, Duc-Hieu Tran, Peter Kairouz, Victor Carbune, Blaise Agüera y Arcas
Can LLMs get help from other LLMs without revealing private information? CoRR (2024)
Amirkeivan Mohtashami, Florian Hartmann, Sian Gooding, Lukas Zilka, Matt Sharifi, Blaise Agüera y Arcas
Social Learning: Towards Collaborative Learning with Large Language Models. CoRR (2023)
Tao Tu, Shekoofeh Azizi, Danny Driess, Mike Schaekermann, Mohamed Amin, Pi-Chuan Chang, Andrew Carroll, Chuck Lau, Ryutaro Tanno, Ira Ktena, Basil Mustafa, Aakanksha Chowdhery, Yun Liu, Simon Kornblith, David J. Fleet, Philip Andrew Mansfield, Sushant Prakash, Renee Wong, Sunny Virmani, Christopher Semturs, S. Sara Mahdavi, Bradley Green, Ewa Dominowska, Blaise Agüera y Arcas, Joelle K. Barral, Dale R. Webster, Gregory S. Corrado, Yossi Matias, Karan Singhal, Pete Florence, Alan Karthikesalingam, Vivek Natarajan
Towards Generalist Biomedical AI. CoRR (2023)
Benjamin Lange, Amanda McCroskery, Ben Zevenbergen, Geoff Keeling, Sandra Blascovich, Kyle Pedersen, Alison Lentz, Blaise Agüera y Arcas
Engaging Google Teams Through Moral Imagination: A Bottom-Up Approach for Responsible Innovation and Ethical Culture Change in Technology Companies. CoRR (2023)
Johannes von Oswald, Eyvind Niklasson, Maximilian Schlegel, Seijin Kobayashi, Nicolas Zucchet, Nino Scherrer, Nolan Miller, Mark Sandler, Blaise Agüera y Arcas, Max Vladymyrov, Razvan Pascanu, João Sacramento
Uncovering mesa-optimization algorithms in Transformers. CoRR (2023)
Karan Singhal, Tao Tu, Juraj Gottweis, Rory Sayres, Ellery Wulczyn, Le Hou, Kevin Clark, Stephen Pfohl, Heather Cole-Lewis, Darlene Neal, Mike Schaekermann, Amy Wang, Mohamed Amin, Sami Lachgar, Philip Andrew Mansfield, Sushant Prakash, Bradley Green, Ewa Dominowska, Blaise Agüera y Arcas, Nenad Tomasev, Yun Liu, Renee Wong, Christopher Semturs, S. Sara Mahdavi, Joelle K. Barral, Dale R. Webster, Gregory S. Corrado, Yossi Matias, Shekoofeh Azizi, Alan Karthikesalingam, Vivek Natarajan
Towards Expert-Level Medical Question Answering with Large Language Models. CoRR (2023)
Zachary Charles, Kallista A. Bonawitz, Stanislav Chiknavaryan, Brendan McMahan, Blaise Agüera y Arcas
Federated Select: A Primitive for Communication- and Memory-Efficient Federated Learning. CoRR (2022)
Karan Singhal, Shekoofeh Azizi, Tao Tu, S. Sara Mahdavi, Jason Wei, Hyung Won Chung, Nathan Scales, Ajay Kumar Tanwani, Heather Cole-Lewis, Stephen Pfohl, Perry Payne, Martin Seneviratne, Paul Gamble, Chris Kelly, Nathaneal Schärli, Aakanksha Chowdhery, Philip Andrew Mansfield, Blaise Agüera y Arcas, Dale R. Webster, Gregory S. Corrado, Yossi Matias, Katherine Chou, Juraj Gottweis, Nenad Tomasev, Yun Liu, Alvin Rajkomar, Joelle K. Barral, Christopher Semturs, Alan Karthikesalingam, Vivek Natarajan
Large Language Models Encode Clinical Knowledge. CoRR (2022)
Mark Sandler, Max Vladymyrov, Andrey Zhmoginov, Nolan Miller, Tom Madams, Andrew Jackson, Blaise Agüera y Arcas
Meta-Learning Bidirectional Update Rules. ICML (2021)
Jianyu Wang, Zachary Charles, Zheng Xu, Gauri Joshi, H. Brendan McMahan, Blaise Agüera y Arcas, Maruan Al-Shedivat, Galen Andrew, Salman Avestimehr, Katharine Daly, Deepesh Data, Suhas N. Diggavi, Hubert Eichner, Advait Gadhikar, Zachary Garrett, Antonious M. Girgis, Filip Hanzely, Andrew Hard, Chaoyang He, Samuel Horvath, Zhouyuan Huo, Alex Ingerman, Martin Jaggi, Tara Javidi, Peter Kairouz, Satyen Kale, Sai Praneeth Karimireddy, Jakub Konecný, Sanmi Koyejo, Tian Li, Luyang Liu, Mehryar Mohri, Hang Qi, Sashank J. Reddi, Peter Richtárik, Karan Singhal, Virginia Smith, Mahdi Soltanolkotabi, Weikang Song, Ananda Theertha Suresh, Sebastian U. Stich, Ameet Talwalkar, Hongyi Wang, Blake E. Woodworth, Shanshan Wu, Felix X. Yu, Honglin Yuan, Manzil Zaheer, Mi Zhang, Tong Zhang, Chunxiang Zheng, Chen Zhu, Wennan Zhu
A Field Guide to Federated Optimization. CoRR (2021)
Adam Sadilek, Luyang Liu, Dung Nguyen, Methun Kamruzzaman, Stylianos Serghiou, Benjamin Rader, Alex Ingerman, Stefan Mellem, Peter Kairouz, Elaine O. Nsoesie, Jamie Macfarlane, Anil Vullikanti, Madhav V. Marathe, Paul Eastham, John S. Brownstein, Blaise Agüera y Arcas, Michael D. Howell, John Hernandez
Privacy-first health research with federated learning. npj Digit. Medicine 4 (2021)
Chongyang Bai, Xiaoxue Zang, Ying Xu, Srinivas Sunkara, Abhinav Rastogi, Jindong Chen, Blaise Agüera y Arcas
UIBert: Learning Generic Multimodal Representations for UI Understanding. CoRR (2021)
Mark Sandler, Max Vladymyrov, Andrey Zhmoginov, Nolan Miller, Andrew Jackson, Tom Madams, Blaise Agüera y Arcas
Meta-Learning Bidirectional Update Rules. CoRR (2021)
Chongyang Bai, Xiaoxue Zang, Ying Xu, Srinivas Sunkara, Abhinav Rastogi, Jindong Chen, Blaise Agüera y Arcas
UIBert: Learning Generic Multimodal Representations for UI Understanding. IJCAI (2021)
Mark Sandler, Andrey Zhmoginov, Liangcheng Luo, Alexander Mordvintsev, Ettore Randazzo, Blaise Agüera y Arcas
Image segmentation via Cellular Automata. CoRR (2020)
Sean Augenstein, H. Brendan McMahan, Daniel Ramage, Swaroop Ramaswamy, Peter Kairouz, Mingqing Chen, Rajiv Mathews, Blaise Agüera y Arcas
Generative Models for Effective ML on Private, Decentralized Datasets. ICLR (2020)
Sean Augenstein, H. Brendan McMahan, Daniel Ramage, Swaroop Ramaswamy, Peter Kairouz, Mingqing Chen, Rajiv Mathews, Blaise Agüera y Arcas
Generative Models for Effective ML on Private, Decentralized Datasets. CoRR (2019)
Blaise Agüera y Arcas
Decentralized Machine Learning. IEEE BigData (2018)
Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, Blaise Agüera y Arcas
Communication-Efficient Learning of Deep Networks from Decentralized Data. AISTATS (2017)
Blaise Agüera y Arcas, Beat Gfeller, Ruiqi Guo, Kevin Kilgour, Sanjiv Kumar, James Lyon, Julian Odell, Marvin Ritter, Dominik Roblek, Matthew Sharifi, Mihajlo Velimirovic
Now Playing: Continuous low-power music recognition. CoRR (2017)
H. Brendan McMahan, Eider Moore, Daniel Ramage, Blaise Agüera y Arcas
Federated Learning of Deep Networks using Model Averaging. CoRR (2016)
Blaise Agüera y Arcas
Machine Intelligence and Human Intelligence. UIST (2015)
Khalid El-Arini, Ulrich Paquet, Ralf Herbrich, Jurgen Van Gael, Blaise Agüera y Arcas
Transparent user models for personalization. KDD (2012)
Sungho Hong, Blaise Agüera y Arcas, Adrienne L. Fairhall
Single Neuron Computation: From Dynamical System to Feature Detector. Neural Comput. 19 (12) (2007)
Blaise Agüera y Arcas, Adrienne L. Fairhall
What Causes a Neuron to Spike? Neural Comput. 15 (8) (2003)
Blaise Agüera y Arcas, Adrienne L. Fairhall, William Bialek
Computation in a Single Neuron: Hodgkin and Huxley Revisited. Neural Comput. 15 (8) (2003)
Blaise Agüera y Arcas, Adrienne L. Fairhall, William Bialek
What Can a Single Neuron Compute? NIPS (2000)