@inproceedings{thorne-etal-2019-fever2,
title = "The {FEVER}2.0 Shared Task",
author = "Thorne, James and
Vlachos, Andreas and
Cocarascu, Oana and
Christodoulopoulos, Christos and
Mittal, Arpit",
editor = "Thorne, James and
Vlachos, Andreas and
Cocarascu, Oana and
Christodoulopoulos, Christos and
Mittal, Arpit",
booktitle = "Proceedings of the Second Workshop on Fact Extraction and VERification (FEVER)",
month = nov,
year = "2019",
address = "Hong Kong, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D19-6601",
doi = "10.18653/v1/D19-6601",
pages = "1--6",
abstract = "We present the results of the second Fact Extraction and VERification (FEVER2.0) Shared Task. The task challenged participants to both build systems to verify factoid claims using evidence retrieved from Wikipedia and to generate adversarial attacks against other participant{'}s systems. The shared task had three phases: \textit{building, breaking and fixing}. There were 8 systems in the builder{'}s round, three of which were new qualifying submissions for this shared task, and 5 adversaries generated instances designed to induce classification errors and one builder submitted a fixed system which had higher FEVER score and resilience than their first submission. All but one newly submitted systems attained FEVER scores higher than the best performing system from the first shared task and under adversarial evaluation, all systems exhibited losses in FEVER score. There was a great variety in adversarial attack types as well as the techniques used to generate the attacks, In this paper, we present the results of the shared task and a summary of the systems, highlighting commonalities and innovations among participating systems.",
}
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%0 Conference Proceedings
%T The FEVER2.0 Shared Task
%A Thorne, James
%A Vlachos, Andreas
%A Cocarascu, Oana
%A Christodoulopoulos, Christos
%A Mittal, Arpit
%Y Thorne, James
%Y Vlachos, Andreas
%Y Cocarascu, Oana
%Y Christodoulopoulos, Christos
%Y Mittal, Arpit
%S Proceedings of the Second Workshop on Fact Extraction and VERification (FEVER)
%D 2019
%8 November
%I Association for Computational Linguistics
%C Hong Kong, China
%F thorne-etal-2019-fever2
%X We present the results of the second Fact Extraction and VERification (FEVER2.0) Shared Task. The task challenged participants to both build systems to verify factoid claims using evidence retrieved from Wikipedia and to generate adversarial attacks against other participant’s systems. The shared task had three phases: building, breaking and fixing. There were 8 systems in the builder’s round, three of which were new qualifying submissions for this shared task, and 5 adversaries generated instances designed to induce classification errors and one builder submitted a fixed system which had higher FEVER score and resilience than their first submission. All but one newly submitted systems attained FEVER scores higher than the best performing system from the first shared task and under adversarial evaluation, all systems exhibited losses in FEVER score. There was a great variety in adversarial attack types as well as the techniques used to generate the attacks, In this paper, we present the results of the shared task and a summary of the systems, highlighting commonalities and innovations among participating systems.
%R 10.18653/v1/D19-6601
%U https://aclanthology.org/D19-6601
%U https://doi.org/10.18653/v1/D19-6601
%P 1-6
Markdown (Informal)
[The FEVER2.0 Shared Task](https://aclanthology.org/D19-6601) (Thorne et al., 2019)
ACL
- James Thorne, Andreas Vlachos, Oana Cocarascu, Christos Christodoulopoulos, and Arpit Mittal. 2019. The FEVER2.0 Shared Task. In Proceedings of the Second Workshop on Fact Extraction and VERification (FEVER), pages 1–6, Hong Kong, China. Association for Computational Linguistics.