Paper

Can Neural Machine Translation be Improved with User Feedback?

We present the first real-world application of methods for improving neural machine translation (NMT) with human reinforcement, based on explicit and implicit user feedback collected on the eBay e-commerce platform. Previous work has been confined to simulation experiments, whereas in this paper we work with real logged feedback for offline bandit learning of NMT parameters... (read more)

Results in Papers With Code
(↓ scroll down to see all results)