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2020 – today
- 2024
[i19]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 abs/2404.01041 (2024)- [i18]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 abs/2404.16244 (2024) - [i17]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 abs/2405.18870 (2024) - [i16]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 abs/2406.19108 (2024) - 2023
- [i15]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 abs/2305.09617 (2023) - [i14]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 abs/2306.06901 (2023) - [i13]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 abs/2307.14334 (2023) - [i12]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 abs/2309.05858 (2023) - [i11]Amirkeivan Mohtashami, Florian Hartmann, Sian Gooding, Lukas Zilka, Matthew Sharifi, Blaise Agüera y Arcas:
Social Learning: Towards Collaborative Learning with Large Language Models. CoRR abs/2312.11441 (2023) - 2022
- [i10]Romal Thoppilan, Daniel De Freitas, Jamie Hall, Noam Shazeer, Apoorv Kulshreshtha, Heng-Tze Cheng, Alicia Jin, Taylor Bos, Leslie Baker, Yu Du, YaGuang Li, Hongrae Lee, Huaixiu Steven Zheng, Amin Ghafouri, Marcelo Menegali, Yanping Huang, Maxim Krikun, Dmitry Lepikhin, James Qin, Dehao Chen, Yuanzhong Xu, Zhifeng Chen, Adam Roberts, Maarten Bosma, Yanqi Zhou, Chung-Ching Chang, Igor Krivokon, Will Rusch, Marc Pickett, Kathleen S. Meier-Hellstern, Meredith Ringel Morris, Tulsee Doshi, Renelito Delos Santos, Toju Duke, Johnny Soraker, Ben Zevenbergen, Vinodkumar Prabhakaran, Mark Diaz, Ben Hutchinson, Kristen Olson, Alejandra Molina, Erin Hoffman-John, Josh Lee, Lora Aroyo, Ravi Rajakumar, Alena Butryna, Matthew Lamm, Viktoriya Kuzmina, Joe Fenton, Aaron Cohen, Rachel Bernstein, Ray Kurzweil, Blaise Agüera y Arcas, Claire Cui, Marian Croak, Ed H. Chi, Quoc Le:
LaMDA: Language Models for Dialog Applications. CoRR abs/2201.08239 (2022) - [i9]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 abs/2208.09432 (2022) - [i8]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 abs/2212.13138 (2022) - 2021
- [j4]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) - [c8]Mark Sandler, Max Vladymyrov, Andrey Zhmoginov, Nolan Miller, Tom Madams, Andrew Jackson, Blaise Agüera y Arcas:
Meta-Learning Bidirectional Update Rules. ICML 2021: 9288-9300 - [c7]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: 1705-1712 - [i7]Mark Sandler, Max Vladymyrov, Andrey Zhmoginov, Nolan Miller, Andrew Jackson, Tom Madams, Blaise Agüera y Arcas:
Meta-Learning Bidirectional Update Rules. CoRR abs/2104.04657 (2021) - [i6]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 Horváth, 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 abs/2107.06917 (2021) - [i5]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 abs/2107.13731 (2021) - 2020
- [c6]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 - [i4]Mark Sandler, Andrey Zhmoginov, Liangcheng Luo, Alexander Mordvintsev, Ettore Randazzo, Blaise Agüera y Arcas:
Image segmentation via Cellular Automata. CoRR abs/2008.04965 (2020)
2010 – 2019
- 2019
- [i3]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 abs/1911.06679 (2019) - 2018
- [c5]Blaise Agüera y Arcas:
Decentralized Machine Learning. IEEE BigData 2018: 1 - 2017
- [c4]Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, Blaise Agüera y Arcas:
Communication-Efficient Learning of Deep Networks from Decentralized Data. AISTATS 2017: 1273-1282 - [i2]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 abs/1711.10958 (2017) - 2016
- [i1]H. Brendan McMahan, Eider Moore, Daniel Ramage, Blaise Agüera y Arcas:
Federated Learning of Deep Networks using Model Averaging. CoRR abs/1602.05629 (2016) - 2015
- [c3]Blaise Agüera y Arcas:
Machine Intelligence and Human Intelligence. UIST 2015: 665 - 2012
- [c2]Khalid El-Arini, Ulrich Paquet, Ralf Herbrich, Jurgen Van Gael, Blaise Agüera y Arcas:
Transparent user models for personalization. KDD 2012: 678-686
2000 – 2009
- 2007
- [j3]Sungho Hong, Blaise Agüera y Arcas, Adrienne L. Fairhall:
Single Neuron Computation: From Dynamical System to Feature Detector. Neural Comput. 19(12): 3133-3172 (2007) - 2003
- [j2]Blaise Agüera y Arcas, Adrienne L. Fairhall, William Bialek:
Computation in a Single Neuron: Hodgkin and Huxley Revisited. Neural Comput. 15(8): 1715-1749 (2003) - [j1]Blaise Agüera y Arcas, Adrienne L. Fairhall:
What Causes a Neuron to Spike? Neural Comput. 15(8): 1789-1807 (2003) - 2000
- [c1]Blaise Agüera y Arcas, Adrienne L. Fairhall, William Bialek:
What Can a Single Neuron Compute? NIPS 2000: 75-81
Coauthor Index
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last updated on 2024-11-07 20:25 CET by the dblp team
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