Neural Unsupervised Domain Adaptation in NLP---A Survey

Understand

Deep neural networks excel at learning from labeled data and achieve state-of-the-art resultson a wide array of Natural Language Processing tasks.

• In contrast, learning from unlabeled data, especially under domain shift, remains a challenge.
• Motivated by the latest advances, in this survey we review neural unsupervised domain adaptation techniques which do not require labeled target domain data.
• This is a more challenging yet a more widely applicable setup.