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 …

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 …

Sampling proper negatives from a large document pool is vital to effectively train a dense
retrieval model. However, existing negative sampling strategies suffer from the uninformative …

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

Conversational search provides users with a natural and convenient new search
experience. Recently, conversational dense retrieval has shown to be a promising …

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

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 …