How to Verify AI-Generated References Before Submission

A plausible citation can still be wrong

AI tools can produce references that look complete while combining fields from different works, changing a title, or attaching a real DOI to the wrong article. A polished citation string is not evidence that the cited work exists or matches the claim.

Start by preserving the reference exactly as the AI produced it. Keep the original wording visible so that any normalization or correction can be reviewed later.

Separate identity checks from formatting

First ask which scholarly work the reference describes. Check whether the DOI resolves, compare the title, authors, venue, year, pages, and other identifiers, and look for contradictions across reliable scholarly records. Only format the citation after the identity is resolved.

A citation formatter can produce a consistent output from incorrect metadata. Formatting is useful at the end of the workflow, not as proof at the beginning.

• Keep the original AI output and the normalized record side by side.
• Prefer exact DOI agreement, but still compare the returned bibliographic fields.
• Use multiple scholarly providers when the record is incomplete or ambiguous.
• Treat a missing DOI as an unresolved question, not automatic evidence of fabrication.
• Escalate near-ties and provider conflicts for human review.

What a useful verification report should show

A reviewable report should identify the selected work, show the sources supporting each field, and keep candidate matches and contradictions visible. A single score can help prioritize work, but it should not hide missing evidence or provider disagreement.

When a correction is proposed, keep it separate from the evidence. Researchers and editors should be able to accept, edit, or reject the proposal before changing a manuscript or bibliography.

Where CiteWise fits

CiteWise can compare an AI-suggested reference with bounded scholarly metadata sources, recover a missing DOI when the evidence supports one, and show field-level evidence for review. It does not claim to identify every AI-generated error automatically, and it does not replace checking the original publication for high-risk decisions.