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TRUE: Re-evaluating Factual Consistency Evaluation

Honovich, Or, Aharoni, Roee, Herzig, Jonathan, Taitelbaum, Hagai, Kukliansy, Doron, Cohen, Vered, Scialom, Thomas, Szpektor, Idan, Hassidim, Avinatan, Matias, Yossi·2022·Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

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Figure 1 ROC AUC when splitting TRUE's data according to the grounding length.
Figure 1 ROC AUC when splitting TRUE's data according to the grounding length.CC-BY · From the PDF
Figure 2 ROC curves for the best performing methods.
Figure 2 ROC curves for the best performing methods.CC-BY · From the PDF

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Citations

Cites

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Metadata

Authors
Honovich, O., Aharoni, R., Herzig, J., Taitelbaum, H., Kukliansy, D., Cohen, V., Scialom, T., Szpektor, I., Hassidim, A., & Matias, Y.
Venue
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Published
2022
Pages
3905-3920
Cited by
58
References
31

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CoChat. (2026). Citation check: TRUE: Re-evaluating Factual Consistency Evaluation. https://app.cochat.ai/papers/10.18653/v1/2022.naacl-main.287
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Honovich, O., Aharoni, R., Herzig, J., Taitelbaum, H., Kukliansy, D., Cohen, V., Scialom, T., Szpektor, I., Hassidim, A., & Matias, Y. (2022). TRUE: Re-evaluating Factual Consistency Evaluation. Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. https://doi.org/10.18653/v1/2022.naacl-main.287

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