Advances and Open Problems in Federated Learning. - Peter Kairouz; H. Brendan McMahan; Brendan Avent; Aurélien Bellet; Mehdi Bennis; Arjun Nitin Bhagoji; Kallista A. Bonawitz; Zachary Charles; Graham Cormode; Rachel Cummings; Rafael G. L. D'Oliveira; Salim El Rouayheb; et al. (CoRR, 2019)

Observer-driven texture analysis in CT imaging. - Matthew A. Kupinski; Zachary Garrett; Jiahua Fan (Image Perception, Observer Performance, and Technology Assessment, 2020)

Adaptive Federated Optimization. - Sashank J. Reddi; Zachary Charles; Manzil Zaheer; Zachary Garrett; Keith Rush; Jakub Konecný; Sanjiv Kumar; Hugh Brendan McMahan (ICLR, 2021)

On Large-Cohort Training for Federated Learning. - Zachary Charles; Zachary Garrett; Zhouyuan Huo; Sergei Shmulyian; Virginia Smith (NeurIPS, 2021)

Federated Reconstruction: Partially Local Federated Learning. - Karan Singhal; Hakim Sidahmed; Zachary Garrett; Shanshan Wu; John Rush; Sushant Prakash (NeurIPS, 2021)

Federated Reconstruction: Partially Local Federated Learning. - Karan Singhal; Hakim Sidahmed; Zachary Garrett; Shanshan Wu; Keith Rush; Sushant Prakash (CoRR, 2021)

Local Adaptivity in Federated Learning: Convergence and Consistency. - Jianyu Wang; Zheng Xu 002; Zachary Garrett; Zachary Charles; Luyang Liu; Gauri Joshi (CoRR, 2021)

A Field Guide to Federated Optimization. - Jianyu Wang; Zachary Charles; Zheng Xu 002; Gauri Joshi; H. Brendan McMahan; Blaise Agüera y Arcas; Maruan Al-Shedivat; Galen Andrew; Salman Avestimehr; Katharine Daly; Deepesh Data; Suhas N. Diggavi; et al. (CoRR, 2021)

Advances and Open Problems in Federated Learning. - Peter Kairouz; H. Brendan McMahan; Brendan Avent; Aurélien Bellet; Mehdi Bennis; Arjun Nitin Bhagoji; Kallista A. Bonawitz; Zachary Charles; Graham Cormode; Rachel Cummings; Rafael G. L. D'Oliveira; Hubert Eichner; et al. (Found. Trends Mach. Learn., 2021)

Does Federated Dropout actually work? - Gary Cheng 004; Zachary Charles; Zachary Garrett; Keith Rush (CVPR Workshops, 2022)

Towards Federated Foundation Models: Scalable Dataset Pipelines for Group-Structured Learning. - Zachary Charles; Nicole Mitchell; Krishna Pillutla; Michael Reneer; Zachary Garrett (NeurIPS, 2023)

Federated Automatic Differentiation. - Keith Rush; Zachary Charles; Zachary Garrett (CoRR, 2023)

FAX: Scalable and Differentiable Federated Primitives in JAX. - Keith Rush; Zachary Charles; Zachary Garrett (CoRR, 2024)

Leveraging Function Space Aggregation for Federated Learning at Scale. - Nikita Dhawan; Nicole Mitchell; Zachary Charles; Zachary Garrett; Gintare Karolina Dziugaite (Trans. Mach. Learn. Res., 2024)

Streaming DiLoCo with overlapping communication: Towards a Distributed Free Lunch. - Arthur Douillard; Yanislav Donchev; Keith Rush; Satyen Kale; Zachary Charles; Zachary Garrett; Gabriel Teston; Dave Lacey; Ross McIlroy; Jiajun Shen; Alexandre Ramé; Arthur Szlam; et al. (CoRR, 2025)

Communication-Efficient Language Model Training Scales Reliably and Robustly: Scaling Laws for DiLoCo. - Zachary Charles; Gabriel Teston; Lucio Dery; Keith Rush; Nova Fallen; Zachary Garrett; Arthur Szlam; Arthur Douillard (CoRR, 2025)

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities. - Gheorghe Comanici; Eric Bieber; Mike Schaekermann; Ice Pasupat; Noveen Sachdeva; Inderjit S. Dhillon; Marcel Blistein; Ori Ram; Dan Zhang; Evan Rosen; Luke Marris; Sam Petulla; et al. (CoRR, 2025)