Why a Citation Checker Should Not Be an LLM
The obvious way to check citations with AI is to ask a model whether they match. It is also the wrong way. Why reference checking has to be deterministic — and where AI genuinely belongs.
Reference integrity for universities and researchers — how CitationLab checks citations against the bibliography, what the Ref[In] Score measures, and how to read the reports.
The obvious way to check citations with AI is to ask a model whether they match. It is also the wrong way. Why reference checking has to be deterministic — and where AI genuinely belongs.
A step-by-step walk through a real reference cross-check — upload, review, de-duplicate, match, and the report at the end. What is free, what costs credits, and which doors close behind you.
Referencing quality is the one dimension of thesis quality universities never measure. The Ref[In] Score turns it into a number — one that is deliberately not a similarity score and not a finding of misconduct.
Practical AI use cases for faculty and doctoral supervisors — from assessment redesign and formative feedback to research supervision, with ethical guardrails that protect academic quality.
How deans, provosts, and education directors can govern, fund, and scale AI in higher education — without sacrificing academic integrity, faculty trust, or student outcomes.