Extended overview of the CLEF 2024 LongEval Lab on Longitudinal Evaluation of Model Performance
Year: 2024
Type: conference-paper
Abstract: We describe the second edition of the LongEval CLEF 2024 shared task. This lab evaluates the temporal persistence of Information Retrieval (IR) systems and Text Classifiers. Task 1 requires IR systems to run on corpora acquired at several timestamps, and evaluates the drop in system quality (NDCG) along these timestamps. Task 2 tackles binary sentiment classification at different points in time, and evaluates the performance drop for different temporal gaps. Overall, 37 teams registered for Task 1 and 25 for Task 2. Ultimately, 14 and 4 teams participated in Task 1 and Task 2, respectively.
Source: Pure (University of Bath)
Authors: Alkhalifa, Rabab, Borkakoty, Hsuvas, Deveaud, Romain, El-Ebshihy, Alaa, Espinosa-Anke, Luis, Fink, Tobias, Galuščáková, Petra, Gonzalez-Saez, Gabriela, Goeuriot, Lorraine, Iommi, David, Liakata, Maria, Madabushi, Harish Tayyar; id_orcid 0000-0001-5260-3653, Medina-Alias, Pablo, Mulhem, Philippe, Piroi, Florina, Popel, Martin, Zubiaga, Arkaitz
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7209825136