most citedExploiting Simulated User Feedback for Conversational Search: Ranking, Rewriting, and Beyond

31 citations · 39 across the 5 of their papers we have counts for

collaborators

5 papers

cs.IR20241 cited

Towards Self-Contained Answers: Entity-Based Answer Rewriting in Conversational Search

Ivan Sekulić, Krisztian Balog, Fabio Crestani

Conversational information-seeking (CIS) is an emerging paradigm for knowledge acquisition and exploratory search. Traditional web search interfaces enable easy exploration of enti…

cs.CL20245 cited

Reliable LLM-based User Simulator for Task-Oriented Dialogue Systems

Ivan Sekulić, Silvia Terragni, Victor Guimarães +5

In the realm of dialogue systems, user simulation techniques have emerged as a game-changer, redefining the evaluation and enhancement of task-oriented dialogue (TOD) systems. Thes…

cs.IR20241 cited

Estimating the Usefulness of Clarifying Questions and Answers for Conversational Search

Ivan Sekulić, Weronika Łajewska, Krisztian Balog +1

While the body of research directed towards constructing and generating clarifying questions in mixed-initiative conversational search systems is vast, research aimed at processing…

cs.IR20241 cited

Analyzing Coherency in Facet-based Clarification Prompt Generation for Search

Oleg Litvinov, Ivan Sekulić, Mohammad Aliannejadi +1

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 i…

cs.IR202331 cited

Exploiting Simulated User Feedback for Conversational Search: Ranking, Rewriting, and Beyond

Paul Owoicho, Ivan Sekulić, Mohammad Aliannejadi +2

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