11 citations · 11 across the 3 of their papers we have counts for
4 papers
Predicting the Success of Domain Adaptation in Text Similarity
Nicolai Pogrebnyakov, Shohreh Shaghaghian
Transfer learning methods, and in particular domain adaptation, help exploit labeled data in one domain to improve the performance of a certain task in another domain. However, it…
Customizing Contextualized Language Models forLegal Document Reviews
Shohreh Shaghaghian, Luna, Feng +2
Inspired by the inductive transfer learning on computer vision, many efforts have been made to train contextualized language models that boost the performance of natural language p…
Unsupervised domain-agnostic identification of product names in social media posts
Nicolai Pogrebnyakov
Product name recognition is a significant practical problem, spurred by the greater availability of platforms for discussing products such as social media and product review functi…
Identifying emergency stages in Facebook posts of police departments with convolutional and recurrent neural networks and support vector machines
Nicolai Pogrebnyakov, Edgar Maldonado
Classification of social media posts in emergency response is an important practical problem: accurate classification can help automate processing of such messages and help other r…