EDBT 2026 Demo / reviewers in the wild / expert
Matteo Cancellieri
dblp:151/7490
· DBLP profile ↗
5ranked-venue papers in the field
1as first author
5since 2021 · last 2026
0000-0002-9558-9772ORCID · verified
Domains — venue-derived; a paper can count in several
Information Retrieval & Web Search · 5 (1 first)
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Evaluating Information Retrieval Models Along Time: The LongEval Lab at CLEF 2026
Timo Breuer 0002, Matteo Cancellieri, Alaa El-Ebshihy, Maik Fröbe, Petra Galuscáková, Lorraine Goeuriot, Gabriel Iturra-Bocaz, Jüri Keller, Petr Knoth, Andreas Konstantin Kruff, Philippe Mulhem, Florina Piroi, David Pride, Philipp Schaer, Didier Schwab |
ECIR (4) | 2 |
| 2025 | Compare: A Framework for Scientific ComparisonsabstractNavigating the vast and rapidly increasing sea of academic publications to identify institutional synergies, benchmark research contributions and pinpoint key research contributions has become an increasingly daunting task, especially with the current exponential increase in new publications. Existing tools provide useful overviews or single-document insights, but none supports structured, qualitative comparisons across institutions or publications. To address this, we demonstrate Compare, a novel framework that tackles this challenge by enabling sophisticated long-context comparisons of scientific contributions. Compare empowers users to explore and analyze research overlaps and differences at both the institutional and publication granularity, all driven by user-defined questions and automatic retrieval over online resources. For this we leverage on Retrieval-Augmented Generation over evolving data sources to foster long context knowledge synthesis. Unlike traditional scientometric tools, Compare goes beyond quantitative indicators by providing qualitative, citation-supported comparisons. Moritz Staudinger, Wojciech Kusa, Matteo Cancellieri, David Pride, Petr Knoth, Allan Hanbury |
CIKM | 3 |
| 2025 | LongEval at CLEF 2025: Longitudinal Evaluation of IR Model Performance
Matteo Cancellieri, Alaa El-Ebshihy, Tobias Fink, Petra Galuscáková, Gabriela González Sáez, Lorraine Goeuriot, David Iommi, Jüri Keller, Petr Knoth, Philippe Mulhem, Florina Piroi, David Pride, Philipp Schaer |
ECIR (5) | 1 |
| 2023 | CORE-GPT: Combining Open Access Research and Large Language Models for Credible, Trustworthy Question Answering
David Pride, Matteo Cancellieri, Petr Knoth |
TPDL | 2 |
| 2022 | Cui Bono? Cumulative Advantage in Open Access Publishing
David Pride, Matteo Cancellieri, Petr Knoth |
TPDL | 2 |