Andrew Hard

According to our database, Andrew Hard authored at least 13 papers between 2018 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

We Are What We Repeatedly Do: Improving Long Context Instruction Following.

Preston K. Robinette, Andrew Hard, Swaroop Ramaswamy, Ehsan Amid, Rajiv Mathews, Taylor T. Johnson

Proceedings of the Findings of the Association for Computational Linguistics: EACL 2026, 2026

2025

MUSIC: MUlti-Step Instruction Contrast for Multi-Turn Reward Models.

Wenzhe Li, Shujian Zhang, Wenxuan Zhou, John Lambert, Chi Jin, Andrew Hard, Rajiv Mathews, Lun Wang

CoRR, December, 2025

Fantastic Reasoning Behaviors and Where to Find Them: Unsupervised Discovery of the Reasoning Process.

Zhenyu Zhang, Shujian Zhang, John Lambert, Wenxuan Zhou, Zhangyang Wang, Mingqing Chen, Andrew Hard, Rajiv Mathews, Lun Wang

CoRR, December, 2025

Eliciting Behaviors in Multi-Turn Conversations.

Jing Huang, Shujian Zhang, Lun Wang, Andrew Hard, Rajiv Mathews, John Lambert

CoRR, December, 2025

Principled Foundations for Preference Optimization.

Wenxuan Zhou, Shujian Zhang, Brice Magdalou, John Lambert, Ehsan Amid, Richard Nock, Andrew Hard

CoRR, July, 2025

2024

Learning from straggler clients in federated learning.

Andrew Hard, Antonious M. Girgis, Ehsan Amid, Sean Augenstein, Lara McConnaughey, Rajiv Mathews, Rohan Anil

CoRR, 2024

2022

Mixed Federated Learning: Joint Decentralized and Centralized Learning.

Sean Augenstein, Andrew Hard, Lin Ning, Karan Singhal, Satyen Kale, Kurt Partridge, Rajiv Mathews

CoRR, 2022

Production federated keyword spotting via distillation, filtering, and joint federated-centralized training.

Andrew Hard, Kurt Partridge, Neng Chen, Sean Augenstein, Aishanee Shah, Hyun Jin Park, Alex Park, Sara Ng, Jessica Nguyen, Ignacio López-Moreno, Rajiv Mathews, Françoise Beaufays

Proceedings of the 23rd Annual Conference of the International Speech Communication Association, 2022

Diurnal or Nocturnal? Federated Learning of Multi-branch Networks from Periodically Shifting Distributions.

Chen Zhu, Zheng Xu, Mingqing Chen, Jakub Konecný, Andrew Hard, Tom Goldstein

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Jointly Learning from Decentralized (Federated) and Centralized Data to Mitigate Distribution Shift.

Sean Augenstein, Andrew Hard, Kurt Partridge, Rajiv Mathews

CoRR, 2021

A Field Guide to Federated Optimization.

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

CoRR, 2021

2020

Training Keyword Spotting Models on Non-IID Data with Federated Learning.

Andrew Hard, Kurt Partridge, Cameron Nguyen, Niranjan Subrahmanya, Aishanee Shah, Pai Zhu, Ignacio López-Moreno, Rajiv Mathews

Proceedings of the 21st Annual Conference of the International Speech Communication Association, 2020

2018

Federated Learning for Mobile Keyboard Prediction.

Andrew Hard, Kanishka Rao, Rajiv Mathews, Françoise Beaufays, Sean Augenstein, Hubert Eichner, Chloé Kiddon, Daniel Ramage

CoRR, 2018