Recommender systems exploit interaction history to estimate user preference, having been
heavily used in a wide range of industry applications. However, static recommendation …

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

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 …

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

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

Conversational question answering (QA) requires the ability to correctly interpret a question
in the context of previous conversation turns. We address the conversational QA task by …

Query rewriting plays a vital role in enhancing conversational search by transforming context-
dependent user queries into standalone forms. Existing approaches primarily leverage …

In conversational search, the user's real search intent for the current turn is dependent on
the previous conversation history. It is challenging to determine a good search query from …

This research aims to explore various methods for assessing user feedback in mixed-
initiative conversational search (CS) systems. While CS systems enjoy profuse …

Compared to standard retrieval tasks, passage retrieval for conversational question
answering (CQA) poses new challenges in understanding the current user question, as …