The latest updates from our Research team.
I presented some preliminary work on using Generative Adversarial Networks to learn distributed representations of documents at the recent NIPS workshop on Adversarial Training. In this post I provide a […]
IntroductionIn this post, AYLIEN NLP Research Intern, Mahdi, talks us through a quick experiment he performed on the back of reading an interesting paper on evolution strategies, by Tim Salimans, […]
Unsupervisedly learned word embeddings have seen tremendous success in numerous NLP tasks in recent years. So much so that in many NLP architectures, they are close to fully replacing more […]
Sentiment analysis is widely used to gauge public opinion towards products, to analyze customer satisfaction, and to detect trends. With the proliferation of customer reviews, more fine-grained aspect-based sentiment analysis […]
There has been a large resurgence of interest in generative models recently (see this blog post by OpenAI for example). These are models that can learn to create data that […]
It is a strong indicator of today’s globalized world and rapidly growing access to Internet platforms, that we have users from over 188 countries and 500 cities globally using our […]