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 …

This research examines the effects of factors such as perceived ease of use, perceived
usefulness, perceived enjoyment, innovativeness, perceived information quality, and …

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 …

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 …

Chatbots are dialog engines for interactive user experience which help by providing
stakeholders such as consumers, device owners, maintenance workers, and so on with real …

Recently, various neural models for multi-party conversation (MPC) have achieved
impressive improvements on a variety of tasks such as addressee recognition, speaker …

Human–computer conversation has long been an interest of artificial intelligence and
natural language processing research. Recent years have seen a dramatic improvement in …

Building an intelligent dialogue system with the ability to select a proper response according
to a multi-turn context is a great challenging task. Existing studies focus on building a context …

Education has been considerably hindered or interrupted as a result of restrictive
regulations and the building of social distance, making it one of the major sectors of COVID …

While participants in a multi-party multi-turn conversation simultaneously engage in multiple
conversation topics, existing response selection methods are developed mainly focusing on …