@inproceedings{chen-etal-2024-semeval,
title = "{S}em{E}val-2024 Task 7: Numeral-Aware Language Understanding and Generation",
author = "Chen, Chung-chi and
Huang, Jian-tao and
Huang, Hen-hsen and
Takamura, Hiroya and
Chen, Hsin-hsi",
editor = {Ojha, Atul Kr. and
Do{\u{g}}ru{\"o}z, A. Seza and
Tayyar Madabushi, Harish and
Da San Martino, Giovanni and
Rosenthal, Sara and
Ros{\'a}, Aiala},
booktitle = "Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)",
month = jun,
year = "2024",
address = "Mexico City, Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.semeval-1.213/",
doi = "10.18653/v1/2024.semeval-1.213",
pages = "1482--1491",
abstract = "Numbers are frequently utilized in both our daily narratives and professional documents, such as clinical notes, scientific papers, financial documents, and legal court orders. The ability to understand and generate numbers is thus one of the essential aspects of evaluating large language models. In this vein, we propose a collection of datasets in SemEval-2024 Task 7 - NumEval. This collection encompasses several tasks focused on numeral-aware instances, including number prediction, natural language inference, question answering, reading comprehension, reasoning, and headline generation. This paper offers an overview of the dataset and presents the results of all subtasks in NumEval. Additionally, we contribute by summarizing participants' methods and conducting an error analysis. To the best of our knowledge, NumEval represents one of the early tasks that perform peer evaluation in SemEval`s history. We will further share observations from this aspect and provide suggestions for future SemEval tasks."
}
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%0 Conference Proceedings
%T SemEval-2024 Task 7: Numeral-Aware Language Understanding and Generation
%A Chen, Chung-chi
%A Huang, Jian-tao
%A Huang, Hen-hsen
%A Takamura, Hiroya
%A Chen, Hsin-hsi
%Y Ojha, Atul Kr.
%Y Doğruöz, A. Seza
%Y Tayyar Madabushi, Harish
%Y Da San Martino, Giovanni
%Y Rosenthal, Sara
%Y Rosá, Aiala
%S Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)
%D 2024
%8 June
%I Association for Computational Linguistics
%C Mexico City, Mexico
%F chen-etal-2024-semeval
%X Numbers are frequently utilized in both our daily narratives and professional documents, such as clinical notes, scientific papers, financial documents, and legal court orders. The ability to understand and generate numbers is thus one of the essential aspects of evaluating large language models. In this vein, we propose a collection of datasets in SemEval-2024 Task 7 - NumEval. This collection encompasses several tasks focused on numeral-aware instances, including number prediction, natural language inference, question answering, reading comprehension, reasoning, and headline generation. This paper offers an overview of the dataset and presents the results of all subtasks in NumEval. Additionally, we contribute by summarizing participants’ methods and conducting an error analysis. To the best of our knowledge, NumEval represents one of the early tasks that perform peer evaluation in SemEval‘s history. We will further share observations from this aspect and provide suggestions for future SemEval tasks.
%R 10.18653/v1/2024.semeval-1.213
%U https://aclanthology.org/2024.semeval-1.213/
%U https://doi.org/10.18653/v1/2024.semeval-1.213
%P 1482-1491
Markdown (Informal)
[SemEval-2024 Task 7: Numeral-Aware Language Understanding and Generation](https://aclanthology.org/2024.semeval-1.213/) (Chen et al., SemEval 2024)
ACL