SEUPD@CLEF: Team IRIS on Temporal Evolution of Query Expansion and Rank Fusion Techniques Applied to Cross-Encoder Re-Rankers

This paper presents how the IRIS group of the Search Engines 2023/2024 course, held at the University of Padua, developed its Information Retrieval system for the Task 1 - LongEval-Retrieval of the LongEval CLEF 2024 Lab, aimed at developing an Information Retrieval (IR) system resilient to temporal evolution of Web documents. To address this challenge, our approach focused on traditional techniques combined with innovative methods. In particular, we focus on cross-encoder re-rankers and analyse Generate, Filter & Fuse (GFF) as a noise reduction technique to improve performance and resilience of Query Expansion (QE) techniques and re-rankers.