Task-oriented dialogue is often decomposed into three tasks: understanding user input,
deciding actions, and generating a response. While such decomposition might suggest a …

Pre-trained language models have been recently shown to benefit task-oriented dialogue
(TOD) systems. Despite their success, existing methods often formulate this task as a …

This paper presents our task-oriented dialog system UBAR which models task-oriented
dialogs on a dialog session level. Specifically, UBAR is acquired by fine-tuning the large pre …

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 …

Existing goal-oriented dialogue datasets focus mainly on identifying slots and values.
However, customer support interactions in reality often involve agents following multi-step …

Medical dialogue generation aims to provide automatic and accurate responses to assist
physicians to obtain diagnosis and treatment suggestions in an efficient manner. In medical …

A task-oriented dialogue system (TOD) is an important application of artificial intelligence. In
the past few years, works on multi-domain TODs have attracted increased research attention …

Images are more than a collection of objects or attributes--they represent a web of
relationships among interconnected objects. Scene Graph has emerged as a new modality …

Training a supervised neural network classifier typically requires many annotated training
samples. Collecting and annotating a large number of data points are costly and sometimes …

End-to-end task-oriented dialog models have achieved promising performance on
collaborative tasks where users willingly coordinate with the system to complete a given …