Neural approaches to conversational AI

J Gao, M Galley, L Li - The 41st international ACM SIGIR conference on …, 2018 - dl.acm.org
This tutorial surveys neural approaches to conversational AI that were developed in the last
few years. We group conversational systems into three categories:(1) question answering …

Deep reinforcement learning: An overview

Y Li - ar** intelligent open-domain dialog systems due to
the availability of large amounts of conversational data and the recent progress on neural …

Deep reinforcement learning

SE Li - Reinforcement learning for sequential decision and …, 2023 - Springer
Similar to humans, RL agents use interactive learning to successfully obtain satisfactory
decision strategies. However, in many cases, it is desirable to learn directly from …

Recent advances and challenges in task-oriented dialog systems

Z Zhang, R Takanobu, Q Zhu, ML Huang… - Science China …, 2020 - Springer
Due to the significance and value in human-computer interaction and natural language
processing, task-oriented dialog systems are attracting more and more attention in both …

A theoretical framework for conversational search

F Radlinski, N Craswell - Proceedings of the 2017 conference on …, 2017 - dl.acm.org
This paper studies conversational approaches to information retrieval, presenting a theory
and model of information interaction in a chat setting. In particular, we consider the question …

Sentiment analysis using deep learning approaches: an overview

O Habimana, Y Li, R Li, X Gu, G Yu - Science China Information Sciences, 2020 - Springer
Nowadays, with the increasing number of Web 2.0 tools, users generate huge amounts of
data in an enormous and dynamic way. In this regard, the sentiment analysis appeared to be …