README.md

metadata

license: other
license_name: composite
pretty_name: VisDocAgentBench
language:
  - en
tags:
  - visual-document-retrieval
  - agentic-search
  - multimodal-retrieval
  - scientific-documents
size_categories:
  - 1K<n<10K
configs:
  - config_name: queries
    data_files:
      - split: test
        path: benchmark/queries.jsonl
  - config_name: evaluator_annotations
    data_files:
      - split: test
        path: benchmark/evaluator_annotations.jsonl
  - config_name: documents
    data_files:
      - split: corpus
        path: corpus/documents.jsonl
  - config_name: pages
    data_files:
      - split: corpus
        path: corpus/pages.jsonl

VisDocAgentBench

VisDocAgentBench is a closed-corpus benchmark for visually rich document retrieval. It contains 120 natural-language queries over 2,375 rendered pages from 100 scientific documents. Queries are evenly divided among direct, one-bridge, and two-bridge evidence structures, with one answer page per query.

[Paper] [Code] [Project page]

Contents

benchmark/
├── queries.jsonl
├── evaluator_annotations.jsonl
└── topics.json
corpus/
├── documents.jsonl
├── pages.jsonl
└── pages/<document_id>/<page_id>.png
dataset_info.json
LICENSES.md

• queries.jsonl contains the query text and topic identifier presented to a retrieval system.
• evaluator_annotations.jsonl contains the answer page, evidence level, and ordered latent support pages used by the evaluator and controlled analyses.
• documents.jsonl records the exact arXiv version, bibliographic metadata, source URLs, source license, page count, and image-availability status for every document.
• pages.jsonl defines all 2,375 page identifiers, document membership, one-based page indices, rendering dimensions, and expected local paths.
• topics.json describes the ten corpus topics.

The standard agent harness reads the query text but does not expose answer or support annotations to the planner.

Dataset Statistics

Statistic	Count
Documents	100
Rendered pages	2,375
Queries	120
Direct queries	40
One-bridge queries	40
Two-bridge queries	40
Unique answer pages	120
Directly included page images	1,469
Locally reconstructed page images	906

Loading the Metadata

Each JSONL component has a distinct schema and can be loaded independently:

from datasets import load_dataset

queries = load_dataset(
    "hulx2002/VisDocAgentBench",
    "queries",
    split="test",
)
annotations = load_dataset(
    "hulx2002/VisDocAgentBench",
    "evaluator_annotations",
    split="test",
)
pages = load_dataset(
    "hulx2002/VisDocAgentBench",
    "pages",
    split="corpus",
)

The complete snapshot can be downloaded with the code repository:

python scripts/download_data.py

Reconstructing the Complete Corpus

The repository includes 1,469 rendered page images whose source licenses permit redistribution. The remaining 906 rows remain in corpus/pages.jsonl with image_included=false. The exact source version and PDF URL are recorded in corpus/documents.jsonl.

After cloning the code repository and downloading this dataset into data/, reconstruct the omitted pages with:

python dataset_tools/download_and_render.py
python dataset_tools/validate_dataset.py --require-complete-corpus

The script downloads each specified arXiv version and renders it at 144 DPI. It verifies the expected page count and dimensions before accepting the reconstructed corpus.

Evaluation

Systems return a ranked list of page identifiers or the opaque page handles assigned by the released agent harness. The evaluator reports Recall@1/3/5/10 and MRR@10 overall and by evidence level. Missing or invalid rankings stay in the 120-query denominator and score zero.

Evaluation code, baseline implementations, deterministic preprocessing, and the full agent tool interfaces are available in the code repository. Generated predictions, traces, OCR caches, embeddings, and model weights are not included in this dataset repository.

Licensing

Benchmark-authored queries, evaluator annotations, topics, and corpus metadata are licensed under CC BY 4.0. Source-document page images retain the license of their source document. The license URL and attribution metadata for every source are recorded in corpus/documents.jsonl.

Page images are included only for 55 CC BY 4.0 documents and 4 CC BY-NC-SA 4.0 documents. Sources under the arXiv nonexclusive distribution license or CC BY-NC-ND 4.0 are represented by metadata and local reconstruction instructions, not redistributed images. See LICENSES.md before reusing source pages.

Citation

@article{hu2026visdocagentbench,
  title={VisDocAgentBench: Benchmarking Agents for Visually Rich Document Retrieval},
  author={Hu, Lexiang and Zhang, Yanzhao and Li, Mingxin and Long, Dingkun and Li, Yikang and Zhang, Fuwei and Wang, Yisen and Lin, Zhouchen},
  journal={arXiv preprint arXiv:2608.17889},
  year={2026}
}