Transformer architectures have revolutionized natural language processing through their
ability to handle longrange dependencies and generate contextually coherent text. Despite …

Dialogue systems are an important and very active research area with many practical
applications. However, researchers and practitioners new to the field may have difficulty with …

Few-shot sequence labeling aims to identify novel classes based on only a few labeled
samples. Existing methods solve the data scarcity problem mainly by designing token-level …

This paper introduces Doc2Bot, a novel dataset for building machines that help users seek
information via conversations. This is of particular interest for companies and organizations …

Users on the internet usually have conversations on interesting facts or topics along with
diverse knowledge from the web. However, most existing knowledge-grounded …

Abstract GLAM (Galleries, Libraries, Archives and Museums) organisations host extensive
digital collections that have been made available to the public for over three decades …

Natural language processing (NLP) aims at investigating the interactions between agents
and humans, processing and analyzing large amounts of natural language data. Large …

Despite a large amount of research into task-oriented dialogue systems, open-ended
dialogue agents have received little attention. Recently, researchers have explored using …

We consider multilingual dialogue systems and ask how the performance of a dialogue
system can be improved by using information that is available in other languages than the …

The knowledge-grounded dialogue task aims to generate responses that convey information
from given knowledge documents. However, it is a challenge for the current sequence …