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 …

There is a resurgent interest in developing intelligent open-domain dialog systems due to
the availability of large amounts of conversational data and the recent progress on neural …

We introduce a multi-task setup of identifying and classifying entities, relations, and
coreference clusters in scientific articles. We create SciERC, a dataset that includes …

We introduce a general framework for several information extraction tasks that share span
representations using dynamically constructed span graphs. The graphs are constructed by …

The majority of conversations a dialogue agent sees over its lifetime occur after it has
already been trained and deployed, leaving a vast store of potential training signal …

Endowing dialogue systems with personas is essential to deliver more human-like
conversations. However, this problem is still far from well explored due to the difficulties of …

Stylistic dialogue response generation, with valuable applications in personality-based
conversational agents, is a challenging task because the response needs to be fluent …

The stylistic properties of text have intrigued computational linguistics researchers in recent
years. Specifically, researchers have investigated the text style transfer task (TST), which …

Most existing works on dialog systems only consider conversation content while neglecting
the personality of the user the bot is interacting with, which begets several unsolved issues …

Although recent neural conversation models have shown great potential, they often
generate bland and generic responses. While various approaches have been explored to …