CLEF 2024 SimpleText Track

verfasst von: Liana Ermakova, Eric SanJuan, Stéphane Huet, Hosein Azarbonyad, Giorgio Maria Di Nunzio, Federica Vezzani, Jennifer D’Souza, Salomon Kabongo, Hamed Babaei Giglou, Yue Zhang, Sören Auer, Jaap Kamps
Abstract: Everyone agrees on the importance of objective scientific information. However, relevant scientific documents tend to be inherently difficult to find and understand either because of intricate terminology or the potential absence of prior knowledge among their readers. Can we improve accessibility for everyone? This paper introduces the SimpleText Track at CLEF 2024, addressing the technical and evaluation challenges associated with making scientific information accessible to a wide audience, including students and non-experts. We provide appropriate reusable data and benchmarks for scientific text summarization and simplification. The CLEF 2024 SimpleText track is based on four interrelated tasks: Task 1 Content Selection: Retrieving Passages to Include in a Simplified Summary. Task 2 Complexity Spotting: Identifying and Explaining Difficult Concepts. Task 3 Text Simplification: Simplify Scientific Text. Task 4 SOTA?: Tracking the State-of-the-Art in Scholarly Publications.
Organisationseinheit(en): Forschungszentrum L3S
Externe Organisation(en): Universität der Westbretagne (UBO)
Universite d'Avignon et des Pays du Vaucluse
Elsevier B.V.
Università degli Studi di Padova
Technische Informationsbibliothek (TIB) Leibniz-Informationszentrum Technik und Naturwissenschaften und Universitätsbibliothek
Technische Universität Berlin
Universiteit van Amsterdam (UvA)
Typ: Aufsatz in Konferenzband
Seiten: 28-35
Anzahl der Seiten: 8
Publikationsdatum: 20.03.2024
Publikationsstatus: Veröffentlicht
Peer-reviewed: Ja
ASJC Scopus Sachgebiete: Theoretische Informatik, Allgemeine Computerwissenschaft
Elektronische Version(en): https://doi.org/10.1007/978-3-031-56072-9_4 (Zugang: Geschlossen)

BibTeX

@inproceedings{47c6d0c208374e3a9cbcb63c66d97198,
title = "CLEF 2024 SimpleText Track",
abstract = "Everyone agrees on the importance of objective scientific information. However, relevant scientific documents tend to be inherently difficult to find and understand either because of intricate terminology or the potential absence of prior knowledge among their readers. Can we improve accessibility for everyone? This paper introduces the SimpleText Track at CLEF 2024, addressing the technical and evaluation challenges associated with making scientific information accessible to a wide audience, including students and non-experts. We provide appropriate reusable data and benchmarks for scientific text summarization and simplification. The CLEF 2024 SimpleText track is based on four interrelated tasks: Task 1 Content Selection: Retrieving Passages to Include in a Simplified Summary. Task 2 Complexity Spotting: Identifying and Explaining Difficult Concepts. Task 3 Text Simplification: Simplify Scientific Text. Task 4 SOTA?: Tracking the State-of-the-Art in Scholarly Publications.",
keywords = "Information extraction, Information retrieval, Natural language processing, Scientific text simplification",
author = "Liana Ermakova and Eric SanJuan and St{\'e}phane Huet and Hosein Azarbonyad and {Di Nunzio}, {Giorgio Maria} and Federica Vezzani and Jennifer D{\textquoteright}Souza and Salomon Kabongo and Giglou, {Hamed Babaei} and Yue Zhang and S{\"o}ren Auer and Jaap Kamps",
note = "Funding Information: We also thank the MaDICS (https://www.madics.fr/ateliers/simpletext/) research group and the French National Research Agency (project ANR-22-CE23-0019-01). SimpleText{\textquoteright}s SOTA Task is jointly funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - project number: NFDI4DataScience (460234259) and the German BMBF project SCINEXT (01lS22070). ; 46th European Conference on Information Retrieval, ECIR 2024 ; Conference date: 24-03-2024 Through 28-03-2024",
year = "2024",
month = mar,
day = "20",
doi = "10.1007/978-3-031-56072-9_4",
language = "English",
isbn = "9783031560712",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "28--35",
editor = "Nazli Goharian and Nicola Tonellotto and Yulan He and Aldo Lipani and Graham McDonald and Craig Macdonald and Iadh Ounis",
booktitle = "Advances in Information Retrieval",
address = "Germany",
}