The 2024 GEM Shared Task on Multilingual Data-to-Text Generation and Summarization: Overview and Preliminary Results

Simon Mille, João Sedoc, Yixin Liu, Elizabeth Clark, Agnes Johanna Axelsson, Miruna Adriana Clinciu, Yufang Hou, Saad Mahamood, Ishmael Nyunya Obonyo, Lining Zhang


Abstract
We present an overview of the GEM 2024 shared task, which comprised of both data-to-text generation and summarization. New datasets were compiled specifically for the task to reduce data contamination in the large language models, which the participants were likely to use. The paper describes the tasks, the datasets, the participating systems, the evaluation methods, and some preliminary results. The full results will be presented at INLG ‘24.
Anthology ID:
2024.inlg-genchal.2
Volume:
Proceedings of the 17th International Natural Language Generation Conference: Generation Challenges
Month:
September
Year:
2024
Address:
Tokyo, Japan
Editors:
Simon Mille, Miruna-Adriana Clinciu
Venue:
INLG
SIG:
SIGGEN
Publisher:
Association for Computational Linguistics
Note:
Pages:
17–38
Language:
URL:
https://aclanthology.org/2024.inlg-genchal.2
DOI:
Bibkey:
Cite (ACL):
Simon Mille, João Sedoc, Yixin Liu, Elizabeth Clark, Agnes Johanna Axelsson, Miruna Adriana Clinciu, Yufang Hou, Saad Mahamood, Ishmael Nyunya Obonyo, and Lining Zhang. 2024. The 2024 GEM Shared Task on Multilingual Data-to-Text Generation and Summarization: Overview and Preliminary Results. In Proceedings of the 17th International Natural Language Generation Conference: Generation Challenges, pages 17–38, Tokyo, Japan. Association for Computational Linguistics.
Cite (Informal):
The 2024 GEM Shared Task on Multilingual Data-to-Text Generation and Summarization: Overview and Preliminary Results (Mille et al., INLG 2024)
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PDF:
https://aclanthology.org/2024.inlg-genchal.2.pdf