This paper presents an in-depth study of ChatGPT, a state-of-the-art language model that is
revolutionizing generative text. We provide a comprehensive analysis of its architecture …

While communicating with a user, a task-oriented dialogue system has to track the user's
needs at each turn according to the conversation history. This process called dialogue state …

Dialogue State Tracking (DST) aims to keep track of users' intentions during the course of a
conversation. In DST, modelling the relations among domains and slots is still an under …

In this paper, we propose to formulate the task-oriented dialogue system as the purely
natural language generation task, so as to fully leverage the large-scale pre-trained models …

Two-phase flow regime identification is an essential transdisciplinary topic that spans digital
signal processing, artificial intelligence, chemical engineering, and energy. Multiphase flow …

The ability to recognise emotions lends a conversational artificial intelligence a human
touch. While emotions in chit-chat dialogues have received substantial attention, emotions in …

The MultiWOZ 2.0 dataset has greatly boosted the research on dialogue state tracking
(DST). However, substantial noise has been discovered in its state annotations. Such noise …

Manually annotating fine-grained slot-value labels for task-oriented dialogue (ToD) systems
is an expensive and time-consuming endeavour. This motivates research into slot-filling …

Spoken dialogue systems (SDS) heavily rely on dialogue state tracking (DST) for success.
However, providing sufficient computational power for training proves challenging, given …

Reasoning about asynchronous plans is challenging since it requires sequential and
parallel planning to optimize time costs. Can large language models (LLMs) succeed at this …