55 citations · 126 across the 6 of their papers we have counts for
4 papers · 1 filter
GRM: Generative Relevance Modeling Using Relevance-Aware Sample Estimation for Document Retrieval
Iain Mackie, Ivan Sekulic, Shubham Chatterjee +2
Recent studies show that Generative Relevance Feedback (GRF), using text generated by Large Language Models (LLMs), can enhance the effectiveness of query expansion. However, LLMs…
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…
User Engagement Prediction for Clarification in Search
Ivan Sekulić, Mohammad Aliannejadi, Fabio Crestani
Clarification is increasingly becoming a vital factor in various topics of information retrieval, such as conversational search and modern Web search engines. Prompting the user fo…
Longformer for MS MARCO Document Re-ranking Task
Ivan Sekulić, Amir Soleimani, Mohammad Aliannejadi +1
Two step document ranking, where the initial retrieval is done by a classical information retrieval method, followed by neural re-ranking model, is the new standard. The best perfo…