Rajiv Mathews
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
17
Venues
7
Active years
2019–2026
Best venue rank
A*
Where they publish
Papers
17 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | EACL | 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 |
| 2026 | EACL | Attacker's Noise Can Manipulate Your Audio-based LLM in the Real World. | Vinu Sankar Sadasivan, Soheil Feizi, Rajiv Mathews, Lun Wang |
| 2024 | ICASSP | FedAQT: Accurate Quantized Training with Federated Learning. | Renkun Ni, Yonghui Xiao, Phoenix Meadowlark, Oleg Rybakov, Tom Goldstein, Ananda Theertha Suresh, Ignacio Lpez-Moreno, Mingqing Chen, Rajiv Mathews |
| 2024 | ICASSP | Unintended Memorization in Large ASR Models, and How to Mitigate It. | Lun Wang, Om Thakkar, Rajiv Mathews |
| 2023 | ASRU | The Gift of Feedback: Improving ASR Model Quality by Learning from User Corrections Through Federated Learning. | Lillian Zhou, Yuxin Ding, Mingqing Chen, Harry Zhang, Rohit Prabhavalkar, Dhruv Guliani, Giovanni Motta, Rajiv Mathews |
| 2023 | ICASSP | Online Model Compression for Federated Learning with Large Models. | Tien-Ju Yang, Yonghui Xiao, Giovanni Motta, Franoise Beaufays, Rajiv Mathews, Mingqing Chen |
| 2022 | ICASSP | A Method to Reveal Speaker Identity in Distributed ASR Training, and How to Counter IT. | Trung Dang, Om Thakkar, Swaroop Ramaswamy, Rajiv Mathews, Peter Chin, Franoise Beaufays |
| 2022 | ICASSP | Capitalization Normalization for Language Modeling with an Accurate and Efficient Hierarchical RNN Model. | Hao Zhang, You-Chi Cheng, Shankar Kumar, W. Ronny Huang, Mingqing Chen, Rajiv Mathews |
| 2022 | ICML | Public Data-Assisted Mirror Descent for Private Model Training. | Ehsan Amid, Arun Ganesh, Rajiv Mathews, Swaroop Ramaswamy, Shuang Song, Thomas Steinke, Vinith M. Suriyakumar, Om Thakkar, Abhradeep Thakurta |
| 2022 | Interspeech | Extracting Targeted Training Data from ASR Models, and How to Mitigate It. | Ehsan Amid, Om Dipakbhai Thakkar, Arun Narayanan, Rajiv Mathews, Franoise Beaufays |
| 2022 | Interspeech | UserLibri: A Dataset for ASR Personalization Using Only Text. | Theresa Breiner, Swaroop Ramaswamy, Ehsan Variani, Shefali Garg, Rajiv Mathews, Khe Chai Sim, Kilol Gupta, Mingqing Chen, Lara McConnaughey |
| 2022 | Interspeech | 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 Lpez-Moreno, Rajiv Mathews, Franoise Beaufays |
| 2022 | Interspeech | Detecting Unintended Memorization in Language-Model-Fused ASR. | W. Ronny Huang, Steve Chien, Om Dipakbhai Thakkar, Rajiv Mathews |
| 2021 | Interspeech | Communication-Efficient Agnostic Federated Averaging. | Jae Ro, Mingqing Chen, Rajiv Mathews, Mehryar Mohri, Ananda Theertha Suresh |
| 2020 | ICLR | Generative Models for Effective ML on Private, Decentralized Datasets. | Sean Augenstein, H. Brendan McMahan, Daniel Ramage, Swaroop Ramaswamy, Peter Kairouz, Mingqing Chen, Rajiv Mathews, Blaise Agera y Arcas |
| 2020 | Interspeech | Training Keyword Spotting Models on Non-IID Data with Federated Learning. | Andrew Hard, Kurt Partridge, Cameron Nguyen, Niranjan Subrahmanya, Aishanee Shah, Pai Zhu, Ignacio Lpez-Moreno, Rajiv Mathews |
| 2019 | CoNLL | Federated Learning of N-Gram Language Models. | Mingqing Chen, Ananda Theertha Suresh, Rajiv Mathews, Adeline Wong, Cyril Allauzen, Franoise Beaufays, Michael Riley |