Dialogue systems are a popular natural language processing (NLP) task as it is promising in
real-life applications. It is also a complicated task since many NLP tasks deserving study are …

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 this paper, we study the problem of employing pre-trained language models for multi-turn
response selection in retrieval-based chatbots. A new model, named Speaker-Aware BERT …

Non-task oriented dialogue systems have achieved great success in recent years due to
largely accessible conversation data and the development of deep learning techniques …

Retrieval-based dialogue systems display an outstanding performance when pre-trained
language models are used, which includes bidirectional encoder representations from …

We focus on multi-turn response selection in a retrieval-based dialog system. In this paper,
we utilize the powerful pre-trained language model Bi-directional Encoder Representations …

Heavily pre-trained transformer models such as BERT have recently shown to be
remarkably powerful at language modelling, achieving impressive results on numerous …

In the retrieval-based multi-turn dialogue modeling, it remains a challenge to select the most
appropriate response according to extracting salient features in context utterances. As a …

In dialog system, dialog act recognition and sentiment classification are two correlative tasks
to capture speakers' intentions, where dialog act and sentiment can indicate the explicit and …

In this paper, we study the task of selecting the optimal response given a user and system
utterance history in retrieval-based multi-turn dialog systems. Recently, pre-trained …