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Version 1.0.0CC BY 4.0No user data

CiteMe Citation Verification Benchmark v1

A frozen, versioned corpus for evaluating whether systems can distinguish real academic references from corrupted and fabricated ones. The 340 labels are known by construction—not inferred from user submissions.

labeled references
340
ground-truth classes
3
languages
4
citation styles
5

What is in corpus-v1

ClassReferences

Correct

EXISTS_CORRECT

Real works whose DOI, title, authors, year, and venue were confirmed.

160

Corrupted

EXISTS_CORRUPTED

Real works with exactly one deterministic metadata corruption.

100

Fabricated

FABRICATED

Constructed citations whose invented titles had no close OpenAlex or Crossref match at build time.

80

Construction and provenance

Correct references begin with public OpenAlex metadata and are retained only after a DOI and title confirmation against Crossref. Corrupted references receive exactly one controlled mutation to the title, year, author, journal, DOI, or pages/volume field.

Fabricated references are synthetic negatives. Their generated titles were checked for close matches in both OpenAlex and Crossref when the corpus was built. The deterministic seed is 20260723.

The corpus covers English, Portuguese, Spanish, and German references in APA, ABNT, Vancouver, Harvard, and MLA styles, including deliberately untidy hand-typed variants and multi-reference bundles.

Scope and limitations

  • • This is an evaluation corpus, not a prevalence estimate for academic writing.
  • • Non-existence checks describe the OpenAlex/Crossref snapshot at build time.
  • • The seed makes transformations deterministic; the frozen files and checksums—not mutable upstream APIs—are the reproducibility anchor.
  • • The separately curated 29 legitimate but unindexed references used in the 369-reference product evaluation are not included in corpus-v1.
  • • Future corrections or additions will be released as a new version; v1 files will not be edited in place.

Use and evaluate

from datasets import load_dataset

data = load_dataset(
    "json",
    data_files="https://citeme.app/datasets/citation-verification-benchmark-v1/corpus-v1.jsonl",
    split="train",
)