3 papers
cs.CL2021
Towards Realistic Single-Task Continuous Learning Research for NER
Justin Payan, Yuval Merhav, He Xie +4
There is an increasing interest in continuous learning (CL), as data privacy is becoming a priority for real-world machine learning applications. Meanwhile, there is still a lack o…
cs.CL2021
Industry Scale Semi-Supervised Learning for Natural Language Understanding
Luoxin Chen, Francisco Garcia, Varun Kumar +2
This paper presents a production Semi-Supervised Learning (SSL) pipeline based on the student-teacher framework, which leverages millions of unlabeled examples to improve Natural L…
cs.CL2019
Efficient Semi-Supervised Learning for Natural Language Understanding by Optimizing Diversity
Eunah Cho, He Xie, John P. Lalor +2
Expanding new functionalities efficiently is an ongoing challenge for single-turn task-oriented dialogue systems. In this work, we explore functionality-specific semi-supervised le…