Datasets:

hotchpotch
/

NanoViDoRe_v3_WIP_converted

configs:
  - config_name: corpus
    data_files:
      - split: computer_science
        path: corpus/computer_science-*
      - split: energy
        path: corpus/energy-*
      - split: finance_en
        path: corpus/finance_en-*
      - split: finance_fr
        path: corpus/finance_fr-*
      - split: hr
        path: corpus/hr-*
      - split: industrial
        path: corpus/industrial-*
      - split: pharmaceuticals
        path: corpus/pharmaceuticals-*
      - split: physics
        path: corpus/physics-*
  - config_name: queries
    data_files:
      - split: computer_science
        path: queries/computer_science-*
      - split: energy
        path: queries/energy-*
      - split: finance_en
        path: queries/finance_en-*
      - split: finance_fr
        path: queries/finance_fr-*
      - split: hr
        path: queries/hr-*
      - split: industrial
        path: queries/industrial-*
      - split: pharmaceuticals
        path: queries/pharmaceuticals-*
      - split: physics
        path: queries/physics-*
  - config_name: qrels
    data_files:
      - split: computer_science
        path: qrels/computer_science-*
      - split: energy
        path: qrels/energy-*
      - split: finance_en
        path: qrels/finance_en-*
      - split: finance_fr
        path: qrels/finance_fr-*
      - split: hr
        path: qrels/hr-*
      - split: industrial
        path: qrels/industrial-*
      - split: pharmaceuticals
        path: qrels/pharmaceuticals-*
      - split: physics
        path: qrels/physics-*
license: other
license_name: vidore-v3-mixed
license_link: https://huggingface.co/collections/vidore/vidore-benchmark-v3
task_categories:
  - visual-document-retrieval
  - text-retrieval
language:
  - en
  - fr
  - de
  - es
  - it
  - pt
tags:
  - nano
  - nanobeir-format
  - vidore
  - wip
pretty_name: NanoViDoRe v3 (WIP, NanoBEIR-format conversion)

NanoViDoRe v3 — WIP NanoBEIR-format conversion

This is a temporary, work-in-progress dataset for experimentation. The format is not final and may change without notice. This repository will be moved, renamed, or deleted in the future (for example, once a canonical location is agreed on). Please do not depend on it for anything long-lived. For the original dataset, use lightonai/NanoViDoRe_v3.

What this is

A re-packaging of lightonai/NanoViDoRe_v3 (revision 0ae74913373848e65871c072831ef30f710642ce) into the same layout as the NanoBEIR datasets (e.g. sentence-transformers/NanoBEIR-en): one split per task, each with its own corpus, queries and qrels.

It was created to explore whether a generic Nano-set evaluator in Sentence Transformers (discussion: huggingface/sentence-transformers#4327) can evaluate visual document retrieval without any dataset-specific loading code.

No content was added, removed or edited. Only the layout and column names changed:

The original shares one 4,000-page corpus across all 8 tasks and separates tasks with a source_dataset column. Every original qrel points to a page of its own source_dataset (0 of 2,061 cross-task qrels), so each page was assigned to the split of its source_dataset. The total number of pages is unchanged (4,000).
Columns were renamed to the NanoBEIR convention. IDs are strings.

Structure

Configs: corpus, queries, qrels. Splits (identical across configs): computer_science, energy, finance_en, finance_fr, hr, industrial, pharmaceuticals, physics.

config	columns
`corpus`	`_id` (str), `text` (str, the OCR `markdown` of the page), `image` (page image)
`queries`	`_id` (str), `text` (str), `language` (str), `query_format` (str)
`qrels`	`query-id` (str), `corpus-id` (str), `score` (int, graded: 1 = critically relevant, 2 = fully relevant)

split	corpus	queries	qrels
computer_science	358	50	227
energy	434	50	200
finance_en	548	50	255
finance_fr	479	50	221
hr	365	50	283
industrial	894	50	320
pharmaceuticals	455	50	226
physics	467	50	329

Queries are spread evenly over 6 languages (en/fr/de/es/it/pt), as in the original.

Usage

from datasets import get_dataset_split_names, load_dataset

dataset_id = "hotchpotch/NanoViDoRe_v3_WIP_converted"
for split in get_dataset_split_names(dataset_id, "qrels"):
    corpus = load_dataset(dataset_id, "corpus", split=split)    # use "image" for visual retrieval, "text" for OCR text
    queries = load_dataset(dataset_id, "queries", split=split)
    qrels = load_dataset(dataset_id, "qrels", split=split)

Scores are not comparable with the original protocol

The original README evaluates every query against the full merged 4,000-page corpus. Here each task only searches its own pages, so pages from other tasks no longer act as extra distractors and scores are somewhat higher.

Example with vidore/colqwen2-v1.0, mean nDCG@10 over the 8 tasks:

setting	binary qrels	graded qrels
original (merged 4,000-page corpus)	0.4663	0.4685
this conversion (per-task corpus)	0.4876	0.4889

License

Same terms as the source datasets. The query/qrels annotations of ViDoRe v3 are released under CC BY 4.0. The page images and their markdown text inherit the license of their original publishers (public domain, CC BY 4.0, Etalab 2.0, CC BY-SA 3.0 and other open reuse licenses); see the documents_metadata config of each ViDoRe v3 dataset for the per-document license.

Citation

Please cite the original works:

@misc{loison2026vidorev3,
  title         = {ViDoRe V3: A Comprehensive Evaluation of Retrieval Augmented Generation in Complex Real-World Scenarios},
  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},
  year          = {2026},
  eprint        = {2601.08620},
  archivePrefix = {arXiv},
  primaryClass  = {cs.AI},
  url           = {https://arxiv.org/abs/2601.08620},
}

The Nano subsampling is by LightOn: lightonai/NanoViDoRe_v3.