Recent years have witnessed a surge of interest in the field of open-domain dialogue.
Thanks to the rapid development of social media, large dialogue corpus from the Internet …

In recent years, fully automated content analysis based on probabilistic topic models has
become popular among social scientists because of their scalability. However, researchers …

To establish an automatic conversation system between humans and computers is regarded
as one of the most hardcore problems in computer science, which involves interdisciplinary …

Sequential data often possesses hierarchical structures with complex dependencies
between sub-sequences, such as found between the utterances in a dialogue. To model …

We introduce a new class of models called multiresolution recurrent neural networks, which
explicitly model natural language generation at multiple levels of abstraction. The models …

This article offers a vision for technology supported collaborative and discussion-based
learning at scale. It begins with historical work in the area of tutorial dialogue systems. It …

Structured belief states are crucial for user goal tracking and database query in task-oriented
dialog systems. However, training belief trackers often requires expensive turn-level …

Inducing a meaningful structural representation from one or a set of dialogues is a crucial
but challenging task in computational linguistics. Advancement made in this area is critical …

To successfully negotiate a deal, it is not enough to communicate fluently: pragmatic
planning of persuasive negotiation strategies is essential. While modern dialogue agents …

Conversation disentanglement aims to separate intermingled messages into detached
sessions, which is a fundamental task in understanding multi-party conversations. Existing …