FreshTab: Sourcing Fresh Data for Table-to-Text Generation Evaluation
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A10511640" target="_blank" >RIV/00216208:11320/25:10511640 - isvavai.cz</a>
Result on the web
<a href="https://aclanthology.org/2025.inlg-main.7" target="_blank" >https://aclanthology.org/2025.inlg-main.7</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
FreshTab: Sourcing Fresh Data for Table-to-Text Generation Evaluation
Original language description
Table-to-text generation (insight generation from tables) is a challenging task that requires precision in analyzing the data. In addition, the evaluation of existing benchmarks is af- fected by contamination of Large Language Model (LLM) training data as well as domain imbalance. We introduce FreshTab, an on-the- fly table-to-text benchmark generation from Wikipedia, to combat the LLM data contam- ination problem and enable domain-sensitive evaluation. While non-English table-to-text datasets are limited, FreshTab collects datasets in different languages on demand (we experi- ment with German, Russian and French in addi- tion to English). We find that insights generated by LLMs from recent tables collected by our method appear clearly worse by automatic met- rics, but this does not translate into LLM and human evaluations. Domain effects are visi- ble in all evaluations, showing that a domain- balanced benchmark is more challenging.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 18th International Natural Language Generation Conference
ISBN
979-8-89176-321-0
ISSN
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e-ISSN
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Number of pages
14
Pages from-to
108-121
Publisher name
Association for Computational Linguistics
Place of publication
Kerrville, TX, USA
Event location
Hanoi, Vietnam
Event date
Oct 29, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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