1 code implementation • 3 Oct 2024 • Piyawat Lertvittayakumjorn, Shanqing Cai, Billy Dou, Cedric Ho, Shumin Zhai
Capacitive touch sensors capture the two-dimensional spatial profile (referred to as a touch heatmap) of a finger's contact with a mobile touchscreen.
no code implementations • 6 Jun 2024 • Renjie Liu, Yanxiang Zhang, Yun Zhu, Haicheng Sun, Yuanbo Zhang, Michael Xuelin Huang, Shanqing Cai, Lei Meng, Shumin Zhai
To obtain models with sufficient quality, we implement a careful data synthetic pipeline tailored to online use cases, design multifaceted metrics, employ a two-stage tuning approach to acquire the dedicated LLM for the feature: the Supervised Fine Tuning (SFT) for foundational quality, followed by the Reinforcement Learning (RL) tuning approach for targeted refinement.
no code implementations • 21 Dec 2023 • Katrin Tomanek, Shanqing Cai, Subhashini Venugopalan
Abbreviation expansion is a strategy used to speed up communication by limiting the amount of typing and using a language model to suggest expansions.
no code implementations • 3 Dec 2023 • Shanqing Cai, Subhashini Venugopalan, Katie Seaver, Xiang Xiao, Katrin Tomanek, Sri Jalasutram, Meredith Ringel Morris, Shaun Kane, Ajit Narayanan, Robert L. MacDonald, Emily Kornman, Daniel Vance, Blair Casey, Steve M. Gleason, Philip Q. Nelson, Michael P. Brenner
A pilot study with 19 non-AAC participants typing on a mobile device by hand demonstrated gains in motor savings in line with the offline simulation, while introducing relatively small effects on overall typing speed.
no code implementations • NAACL 2022 • Shanqing Cai, Subhashini Venugopalan, Katrin Tomanek, Ajit Narayanan, Meredith Ringel Morris, Michael P. Brenner
Motivated by the need for accelerating text entry in augmentative and alternative communication (AAC) for people with severe motor impairments, we propose a paradigm in which phrases are abbreviated aggressively as primarily word-initial letters.
1 code implementation • 27 Feb 2019 • Akshay Agrawal, Akshay Naresh Modi, Alexandre Passos, Allen Lavoie, Ashish Agarwal, Asim Shankar, Igor Ganichev, Josh Levenberg, Mingsheng Hong, Rajat Monga, Shanqing Cai
TensorFlow Eager is a multi-stage, Python-embedded domain-specific language for hardware-accelerated machine learning, suitable for both interactive research and production.
no code implementations • 16 Jan 2019 • Daniel Smilkov, Nikhil Thorat, Yannick Assogba, Ann Yuan, Nick Kreeger, Ping Yu, Kangyi Zhang, Shanqing Cai, Eric Nielsen, David Soergel, Stan Bileschi, Michael Terry, Charles Nicholson, Sandeep N. Gupta, Sarah Sirajuddin, D. Sculley, Rajat Monga, Greg Corrado, Fernanda B. Viégas, Martin Wattenberg
TensorFlow. js is a library for building and executing machine learning algorithms in JavaScript.