As a primary means of information acquisition, information retrieval (IR) systems, such as
search engines, have integrated themselves into our daily lives. These systems also serve …

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

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 …

Query performance prediction (QPP) is a core task in information retrieval. The QPP task is
to predict the retrieval quality of a search system for a query without relevance judgments …

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

Conversational search allows a user to interact with a search system in multiple turns. A
query is strongly dependent on the conversation context. An effective way to improve …

Conversational search facilitates complex information retrieval by enabling multi-turn
interactions between users and the system. Supporting such interactions requires a …

Conversational search supports multi-turn user-system interactions to solve complex
information needs. Different from the traditional single-turn ad-hoc search, conversational …

Conversational query rewriting (CQR) realizes conversational search by reformulating the
search dialogue into a standalone rewrite. However, existing CQR models either are not …

Personalized conversational information retrieval (CIR) combines conversational and
personalizable elements to satisfy various users' complex information needs through multi …