ReferenceVerify
Go ProSign in TR EN

Is your bibliography really correct?

Paste your references or upload a document; we check each one against scholarly records.

Writing in Word? Install the Word add-in and check without leaving your document →
How to use this tool

Paste a reference list (or upload a .txt/.docx/.pdf) and we verify each entry against scholarly databases, catching fabricated, mismatched, retracted or wrongly-formatted citations.

  1. Paste your references, or upload a file. From a full paper we auto-detect the bibliography section. .bib/.ris imports are also supported.
  2. Click “Verify”. Each reference is checked for reality (DOI / year / authors / journal), for formatting, and against the retraction database.
  3. Read the result: a colored badge (Verified / Unverified / Suspicious) and a 0–100 confidence score per entry.
  4. Click any citation to see the matched source record and where it was found.
  5. Download the check report (Word) or export as CSV, BibTeX or RIS. To restyle the citations and references in your Word file, use the “Reference style” tab.
Full guide & PDF →

Your text is processed in your browser and is never sent to Turnitin or any other plagiarism database. Reports are kept in My activity only for members, when “save to my account” is ticked.

Used by journal editors and researchers at 140+ universities and institutions.

2026 study: 41/93 approved theses had a broken DOI · readOne thesis? Thesis pack $6 / 7 days

What you get back

Every reference is searched in the academic indexes and marked with one of four outcomes:

Fine#1

Vaswani, A., et al. (2017). Attention is all you need. Advances in Neural Information Processing Systems, 30.

A record was found and the title, authors and year match. The reference is real; nothing to do.

Needs fixing#2

LeCun, Y., Bengio, Y., & Hinton, G. (2016). Deep learning. Nature, 521(7553), 436-444.

The work is real but the year is wrong (record: 2015). Copy the correct reference in one click.

Unverified#3

Devlin, J., et al. (2018). BERT: Pre-training of deep bidirectional transformers for language understanding. NAACL.

No certain match: the title fits, the year differs (record: 2019). Check it before submitting.

Suspicious#4

Doe, J. (2023). A novel approach to early cancer diagnosis with deep learning. Journal of AI in Medicine, 12(3), 45-60. https://doi.org/10.1234/jaim.2023.045

No match in any scholarly database and the DOI does not resolve. Most likely fabricated.