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https://doi.org/10.21256/zhaw-29046| Publikationstyp: | Konferenz: Paper |
| Art der Begutachtung: | Peer review (Publikation) |
| Titel: | ZHAW-CAI at CheckThat! 2023 : ensembling using kernel averaging |
| Autor/-in: | von Däniken, Pius Deriu, Jan Milan Cieliebak, Mark |
| et. al: | No |
| DOI: | 10.21256/zhaw-29046 |
| Tagungsband: | Working Notes of the Conference and Labs of the Evaluation Forum (CLEF 2023) |
| Herausgeber/-in des übergeordneten Werkes: | Aliannejadi, Mohammad Faggioli, Guglielmo Ferro, Nicola Vlachos, Michalis |
| Seite(n): | 534 |
| Seiten bis: | 545 |
| Angaben zur Konferenz: | 14th Conference and Labs of the Evaluation Forum (CLEF), Thessaloniki, Greece, 18-21 September 2023 |
| Erscheinungsdatum: | 2023 |
| Reihe: | CEUR Workshop Proceedings |
| Reihenzählung: | 3497 |
| Verlag / Hrsg. Institution: | CEUR Workshop Proceedings |
| ISSN: | 1613-0073 |
| Andere Identifier: | urn:nbn:de:0074-3497-0 |
| Sprache: | Englisch |
| Schlagwörter: | Multi-modal; Claim check-worthiness; Multiple kernel learning; Fact checking |
| Fachgebiet (DDC): | 410.285: Computerlinguistik |
| Zusammenfassung: | We describe our approaches to sub-task 1A on multi-modal check-worthiness classification of the CheckThat! Lab 2023 in English. The goal was to determine whether a tweet is worth fact-checking based on its text and image content. Our submission was based on a kernel ensemble of different uni-modal and multi-modal classifiers. It achieved second place out of 7 teams with an F1 score of 0.708. |
| URI: | https://ceur-ws.org/Vol-3497/paper-048.pdf https://digitalcollection.zhaw.ch/handle/11475/29046 |
| Volltext Version: | Publizierte Version |
| Lizenz (gemäss Verlagsvertrag): | CC BY 4.0: Namensnennung 4.0 International |
| Departement: | School of Engineering |
| Organisationseinheit: | Centre for Artificial Intelligence (CAI) |
| Enthalten in den Sammlungen: | Publikationen School of Engineering |
Dateien zu dieser Ressource:
| Datei | Beschreibung | Größe | Format | |
|---|---|---|---|---|
| 2023_vonDaeniken-etal_ZHAW-CAI-at-CheckThat-2023.pdf | 578.67 kB | Adobe PDF |  Öffnen/Anzeigen |
Zur Langanzeige
von Däniken, P., Deriu, J. M., & Cieliebak, M. (2023). ZHAW-CAI at CheckThat! 2023 : ensembling using kernel averaging [Conference paper]. In M. Aliannejadi, G. Faggioli, N. Ferro, & M. Vlachos (Eds.), Working Notes of the Conference and Labs of the Evaluation Forum (CLEF 2023) (pp. 534–545). CEUR Workshop Proceedings. https://doi.org/10.21256/zhaw-29046
von Däniken, P., Deriu, J.M. and Cieliebak, M. (2023) ‘ZHAW-CAI at CheckThat! 2023 : ensembling using kernel averaging’, in M. Aliannejadi et al. (eds) Working Notes of the Conference and Labs of the Evaluation Forum (CLEF 2023). CEUR Workshop Proceedings, pp. 534–545. Available at: https://doi.org/10.21256/zhaw-29046.
P. von Däniken, J. M. Deriu, and M. Cieliebak, “ZHAW-CAI at CheckThat! 2023 : ensembling using kernel averaging,” in Working Notes of the Conference and Labs of the Evaluation Forum (CLEF 2023), 2023, pp. 534–545. doi: 10.21256/zhaw-29046.
VON DÄNIKEN, Pius, Jan Milan DERIU und Mark CIELIEBAK, 2023. ZHAW-CAI at CheckThat! 2023 : ensembling using kernel averaging. In: Mohammad ALIANNEJADI, Guglielmo FAGGIOLI, Nicola FERRO und Michalis VLACHOS (Hrsg.), Working Notes of the Conference and Labs of the Evaluation Forum (CLEF 2023) [online]. Conference paper. CEUR Workshop Proceedings. 2023. S. 534–545. Verfügbar unter: https://ceur-ws.org/Vol-3497/paper-048.pdf
von Däniken, Pius, Jan Milan Deriu, and Mark Cieliebak. 2023. “ZHAW-CAI at CheckThat! 2023 : Ensembling Using Kernel Averaging.” Conference paper. In Working Notes of the Conference and Labs of the Evaluation Forum (CLEF 2023), edited by Mohammad Aliannejadi, Guglielmo Faggioli, Nicola Ferro, and Michalis Vlachos, 534–45. CEUR Workshop Proceedings. https://doi.org/10.21256/zhaw-29046.
von Däniken, Pius, et al. “ZHAW-CAI at CheckThat! 2023 : Ensembling Using Kernel Averaging.” Working Notes of the Conference and Labs of the Evaluation Forum (CLEF 2023), edited by Mohammad Aliannejadi et al., CEUR Workshop Proceedings, 2023, pp. 534–45, https://doi.org/10.21256/zhaw-29046.
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