@inproceedings{pratapa-etal-2020-constrained,
title = "{C}onstrained {F}act {V}erification for {FEVER}",
author = "Pratapa, Adithya and
Jayanthi, Sai Muralidhar and
Nerella, Kavya",
editor = "Webber, Bonnie and
Cohn, Trevor and
He, Yulan and
Liu, Yang",
booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)",
month = nov,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.emnlp-main.629",
doi = "10.18653/v1/2020.emnlp-main.629",
pages = "7826--7832",
abstract = "Fact-verification systems are well explored in the NLP literature with growing attention owing to shared tasks like FEVER. Though the task requires reasoning on extracted evidence to verify a claim{'}s factuality, there is little work on understanding the reasoning process. In this work, we propose a new methodology for fact-verification, specifically FEVER, that enforces a closed-world reliance on extracted evidence. We present an extensive evaluation of state-of-the-art verification models under these constraints.",
}
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%0 Conference Proceedings
%T Constrained Fact Verification for FEVER
%A Pratapa, Adithya
%A Jayanthi, Sai Muralidhar
%A Nerella, Kavya
%Y Webber, Bonnie
%Y Cohn, Trevor
%Y He, Yulan
%Y Liu, Yang
%S Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
%D 2020
%8 November
%I Association for Computational Linguistics
%C Online
%F pratapa-etal-2020-constrained
%X Fact-verification systems are well explored in the NLP literature with growing attention owing to shared tasks like FEVER. Though the task requires reasoning on extracted evidence to verify a claim’s factuality, there is little work on understanding the reasoning process. In this work, we propose a new methodology for fact-verification, specifically FEVER, that enforces a closed-world reliance on extracted evidence. We present an extensive evaluation of state-of-the-art verification models under these constraints.
%R 10.18653/v1/2020.emnlp-main.629
%U https://aclanthology.org/2020.emnlp-main.629
%U https://doi.org/10.18653/v1/2020.emnlp-main.629
%P 7826-7832
Markdown (Informal)
[Constrained Fact Verification for FEVER](https://aclanthology.org/2020.emnlp-main.629) (Pratapa et al., EMNLP 2020)
ACL
- Adithya Pratapa, Sai Muralidhar Jayanthi, and Kavya Nerella. 2020. Constrained Fact Verification for FEVER. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 7826–7832, Online. Association for Computational Linguistics.