Two tools, one mission: catch AI-hallucinated citations before they reach your paper, and find real sources that actually support your argument.
Catch hallucinated, mismatched, or broken citations before a reviewer does.
Whether you upload a BibTeX file, an RIS export, or paste raw text, our system first needs to understand your data. We use advanced parsing algorithms to identify citation styles (APA, MLA, Chicago, Vancouver, IEEE) and extract key metadata: Titles, Authors, Publication Years, and DOIs.
This is the core of our citation verification process. Unlike simple format checkers, AccuraCite queries massive, authoritative academic databases in real-time. We don't just check if the link works; we verify that the paper actually exists in the scholarly record.
We waterfall your request through multiple providers to ensure maximum coverage, from Computer Science preprints to Biomedical journals.
AI models (like ChatGPT) often generate "hallucinated" citations—papers that look real but don't exist. They might combine a real author with a fake title.
AccuraCite uses fuzzy string matching to detect these discrepancies. If a paper is found but the author is wrong, we flag it as a Mismatch. If no record exists across all databases, we flag it as a Hallucination.
If you made a typo or if an AI hallucinated a title slightly, our system attempts to find the correct paper. We analyze similarity scores to suggest the real source you likely intended to cite.
For non-academic sources (like software documentation or blogs), we perform a Direct URL Verification to ensure the webpage is live and relevant, preventing false alarms for valid web references.
No bibliography yet? Paste a statement and get real, claim-relevant citations back.
You paste a thesis, claim, or paragraph and mark each spot that needs a source with \cite(n). We segment your text and identify exactly what each citation request needs to support.
We query the same academic databases used for verification, but we go a step further: we read the full abstract of each candidate paper, not just its title, and use Large Language Models specifically prompted to retrieve real sources rather than hallucinate them. Papers that merely share keywords with your claim — without actually supporting it — are filtered out.
The system constructs valid BibTeX entries with correct authors, years, and DOIs for every match you accept, so you can drop them straight into your reference manager or paper — a solid foundation for your arguments.
Verify your bibliography or find real, claim-relevant sources — both free, in seconds.