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 …

As a cornerstone of modern information access, search engines have become
indispensable in everyday life. With the rapid advancements in AI and natural language …

The ability to understand a user's underlying needs is critical for conversational systems,
especially with limited input from users in a conversation. Thus, in such a domain, Asking …

Large language models (LLMs) have demonstrated impressive capabilities in various
natural language processing tasks. Despite this, their application to information retrieval (IR) …

The effectiveness of clarification question models in engaging users within search systems
is currently constrained, casting doubt on their overall usefulness. To improve the …

Generating diverse and effective clarifying questions is crucial for improving query
understanding and retrieval performance in open-domain conversational search (CS) …

Clarifying questions are an integral component of modern information retrieval systems,
directly impacting user satisfaction and overall system performance. Poorly formulated …

In mixed-initiative conversational search systems, clarifying questions aid users who
struggle to express their intentions in a single query. These questions aim to uncover user's …

Clarifying user's information needs is an essential component of modern search systems.
While most of the approaches for constructing clarifying prompts rely on query facets, the …

Generating clarifying questions can effectively clarify users' complicated search intent in
conversational search systems. However, existing methods based on pre-defined templates …