Team SaarLST at the GEM’24 D2T Task: Symbolic retrieval substantially reduces hallucination in data-to-text generation

Mayank Jobanputra, Vera Demberg


Anthology ID:
2025.inlg-genchal.4
Volume:
Proceedings of the 18th International Natural Language Generation Conference: Generation Challenges
Month:
October
Year:
2025
Address:
Hanoi, Vietnam
Editor:
Simon Mille
Venue:
INLG
SIG:
SIGGEN
Publisher:
Association for Computational Linguistics
Note:
Pages:
48–50
Language:
URL:
https://preview.aclanthology.org/ingest-luhme/2025.inlg-genchal.4/
DOI:
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Cite (ACL):
Mayank Jobanputra and Vera Demberg. 2025. Team SaarLST at the GEM’24 D2T Task: Symbolic retrieval substantially reduces hallucination in data-to-text generation. In Proceedings of the 18th International Natural Language Generation Conference: Generation Challenges, pages 48–50, Hanoi, Vietnam. Association for Computational Linguistics.
Cite (Informal):
Team SaarLST at the GEM’24 D2T Task: Symbolic retrieval substantially reduces hallucination in data-to-text generation (Jobanputra & Demberg, INLG 2025)
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https://preview.aclanthology.org/ingest-luhme/2025.inlg-genchal.4.pdf