@inproceedings{cunha-etal-2024-imaginary,
title = "Imaginary Numbers! Evaluating Numerical Referring Expressions by Neural End-to-End Surface Realization Systems",
author = "Cunha, Rossana and
Chinonso, Osuji and
Campos, Jo{\~a}o and
Timoney, Brian and
Davis, Brian and
Cozman, Fabio and
Pagano, Adriana and
Castro Ferreira, Thiago",
editor = "Tafreshi, Shabnam and
Akula, Arjun and
Sedoc, Jo{\~a}o and
Drozd, Aleksandr and
Rogers, Anna and
Rumshisky, Anna",
booktitle = "Proceedings of the Fifth Workshop on Insights from Negative Results in NLP",
month = jun,
year = "2024",
address = "Mexico City, Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.insights-1.10",
doi = "10.18653/v1/2024.insights-1.10",
pages = "73--81",
abstract = "Neural end-to-end surface realizers output more fluent texts than classical architectures. However, they tend to suffer from adequacy problems, in particular hallucinations in numerical referring expression generation. This poses a problem to language generation in sensitive domains, as is the case of robot journalism covering COVID-19 and Amazon deforestation. We propose an approach whereby numerical referring expressions are converted from digits to plain word form descriptions prior to being fed to state-of-the-art Large Language Models. We conduct automatic and human evaluations to report the best strategy to numerical superficial realization. Code and data are publicly available.",
}
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%0 Conference Proceedings
%T Imaginary Numbers! Evaluating Numerical Referring Expressions by Neural End-to-End Surface Realization Systems
%A Cunha, Rossana
%A Chinonso, Osuji
%A Campos, João
%A Timoney, Brian
%A Davis, Brian
%A Cozman, Fabio
%A Pagano, Adriana
%A Castro Ferreira, Thiago
%Y Tafreshi, Shabnam
%Y Akula, Arjun
%Y Sedoc, João
%Y Drozd, Aleksandr
%Y Rogers, Anna
%Y Rumshisky, Anna
%S Proceedings of the Fifth Workshop on Insights from Negative Results in NLP
%D 2024
%8 June
%I Association for Computational Linguistics
%C Mexico City, Mexico
%F cunha-etal-2024-imaginary
%X Neural end-to-end surface realizers output more fluent texts than classical architectures. However, they tend to suffer from adequacy problems, in particular hallucinations in numerical referring expression generation. This poses a problem to language generation in sensitive domains, as is the case of robot journalism covering COVID-19 and Amazon deforestation. We propose an approach whereby numerical referring expressions are converted from digits to plain word form descriptions prior to being fed to state-of-the-art Large Language Models. We conduct automatic and human evaluations to report the best strategy to numerical superficial realization. Code and data are publicly available.
%R 10.18653/v1/2024.insights-1.10
%U https://aclanthology.org/2024.insights-1.10
%U https://doi.org/10.18653/v1/2024.insights-1.10
%P 73-81
Markdown (Informal)
[Imaginary Numbers! Evaluating Numerical Referring Expressions by Neural End-to-End Surface Realization Systems](https://aclanthology.org/2024.insights-1.10) (Cunha et al., insights-WS 2024)
ACL
- Rossana Cunha, Osuji Chinonso, João Campos, Brian Timoney, Brian Davis, Fabio Cozman, Adriana Pagano, and Thiago Castro Ferreira. 2024. Imaginary Numbers! Evaluating Numerical Referring Expressions by Neural End-to-End Surface Realization Systems. In Proceedings of the Fifth Workshop on Insights from Negative Results in NLP, pages 73–81, Mexico City, Mexico. Association for Computational Linguistics.