
Shanqing Cai
Shanqing Cai is a Staff Software Engineer at Google. His current research areas include machine learning, large language models (LLMs), human-computer interfaces for text-entry, and accessibility.
Authored Publications
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Google
Can Capacitive Touch Images Enhance Mobile Keyboard Decoding?
Billy Dou
Cedric Ho
Proceedings of UIST 2024 (2024)
Using large language models to accelerate communication for eye gaze typing users with ALS
Subhashini Venugopalan
Katie Seaver
Xiang Xiao
Katrin Tomanek
Sri Jalasutram
Ajit Narayanan
Bob MacDonald
Emily Kornman
Daniel Vance
Blair Casey
Steve Gleason
(2024)
Rambler: Supporting Writing With Speech via LLM-Assisted Gist Manipulation
Susan Lin
Jeremy Warner
J.D. Zamfirescu-Pereira
Matthew G Lee
Sauhard Jain
Michael Xuelin Huang
Bjoern Hartmann
Can Liu
Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems, Association for Computing Machinery, New York, NY, USA
SkipWriter: LLM-Powered Abbreviated Writing on Tablets
Zheer Xu
Mukund Varma T
Proceedings of UIST 2024 (2024)
SpeakFaster Observer: Long-Term Instrumentation of Eye-Gaze Typing for Measuring AAC Communication
Katrin Tomanek
Richard Jonathan Noel Cave
Bob MacDonald
Jon Campbell
Blair Casey
Emily Kornman
Daniel Vance
Jay Beavers
CHI23 Case Studies of HCI in Practice (2023) (to appear)
Context-Aware Abbreviation Expansion Using Large Language Models
Katrin Tomanek
Ajit Narayanan
Annual Conference of the North American Chapter of the Association for Computational Linguistics, 2022 (2022) (to appear)
A Voice-Activated Switch for Persons with Motor and Speech Impairments: Isolated-Vowel Spotting Using Neural Networks
Lisie Lillianfeld
Katie Seaver
Jordan R. Green
D. Sculley
InterSpeech 2021 (2021)
TensorFlow.js: Machine Learning for the Web and Beyond
Daniel Smilkov
Nikhil Thorat
Yannick Assogba
Ann Yuan
Nick Kreeger
Ping Yu
Kangyi Zhang
Eric Nielsen
Stan Bileschi
Charles Nicholson
Sandeep N. Gupta
Sarah Sirajuddin
D. Sculley
Rajat Monga
SysML, Palo Alto, CA, USA (2019)
TensorFlow Debugger: Debugging Dataflow Graphs for Machine Learning
Eric Nielsen
Michael Salib
D. Sculley
Proceedings of the Reliable Machine Learning in the Wild - NIPS 2016 Workshop (2016)