ViDoRe V3
Visual document retrieval across multi-modal enterprise documents spanning finance, industrial, computer science, pharmaceutical, and other professional domains. Includes both open and closed datasets; to submit results on private tasks, please open an issue.
Reference paper →Cite this benchmark
Citation (BibTeX)
@article{loison2026vidorev3comprehensiveevaluation,
archiveprefix = {arXiv},
author = {António Loison and Quentin Macé and Antoine Edy and Victor Xing and Tom Balough and Gabriel Moreira and Bo Liu and Manuel Faysse and Céline Hudelot and Gautier Viaud},
eprint = {2601.08620},
primaryclass = {cs.AI},
title = {ViDoRe V3: A Comprehensive Evaluation of Retrieval Augmented Generation in Complex Real-World Scenarios},
url = {https://arxiv.org/abs/2601.08620},
year = {2026},
}
Languages 6
Tasks 10
Task Types 1
Models 0