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Publicatie
Understanding the Impact of Evidence-Aware Sentence Selection for Fact Checking
Boekbijdrage - Boekhoofdstuk Conferentiebijdrage
Fact Extraction and VERification (FEVER) is a recently introduced task that consists of the following subtasks (i) document retrieval, (ii) sentence retrieval, and (iii) claim verification. In this work, we focus on the subtask of sentence retrieval. Specifically, we propose an evidence-aware transformer-based model that outperforms all other models in terms of FEVER score by using a subset of training instances. In addition, we conduct a large experimental study to get a better understanding of the problem, while we summarize our findings by presenting future research challenges.
Boek: Proceedings of the Fourth Workshop on NLP for Internet Freedom: Censorship, Disinformation, and Propaganda
Series: NLP4IF 2021 - NLP for Internet Freedom: Censorship, Disinformation, and Propaganda, Proceedings of the 4th Workshop
Pagina's: 23-28
Aantal pagina's: 6
Jaar van publicatie:2021