Building dialogue systems that naturally converse with humans is being an attractive and an active research domain. Multiple systems are being designed everyday and several datasets are being available. For this reason, it is being hard to keep an up-to-date state-of-the-art. In this work, we present the latest and most relevant retrieval-based dialogue systems and the available datasets used to build and evaluate them. We discuss their limitations and provide insights and guidelines for future work.
@article{arxiv.1907.12878,
title = {Deep Retrieval-Based Dialogue Systems: A Short Review},
author = {Basma El Amel Boussaha and Nicolas Hernandez and Christine Jacquin and Emmanuel Morin},
journal= {arXiv preprint arXiv:1907.12878},
year = {2019}
}