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 …

Alongside huge volumes of research on deep learning models in NLP in the recent years,
there has been much work on benchmark datasets needed to track modeling progress …

The goal of text ranking is to generate an ordered list of texts retrieved from a corpus in
response to a query. Although the most common formulation of text ranking is search …

Conversational information seeking (CIS) is concerned with a sequence of interactions
between one or more users and an information system. Interactions in CIS are primarily …

Dense retrieval (DR) has the potential to resolve the query understanding challenge in
conversational search by matching in the learned embedding space. However, this …

In a conversational question answering scenario, a questioner seeks to extract information
about a topic through a series of interdependent questions and answers. As the …

ChatGPT and similar large language model (LLM) based conversational agents have
brought shock waves to the research world. Although astonished by their human-like …

The advent of recent Natural Language Processing technology has led human and machine
interactions more toward conversation. In Conversational Search Systems (CSS) like …

Many important questions (eg" How to eat healthier?") require conversation to establish
context and explore in depth. However, conversational question answering (ConvQA) …

Precisely understanding users' contextual search intent has been an important challenge for
conversational search. As conversational search sessions are much more diverse and long …