Skip to content
AI-assisted publishing

Keep AI-assisted publishing traceable to its sources.

Generative AI can help research, summarize, synthesize, draft, and rewrite. But when factual or source-dependent claims survive into publication, the external evidence behind them should remain identifiable through publisher-controlled references that are separate from the generated prose.

For publishers using AI somewhere between source material and the finished article.
Published claim Reference retained
External report, study, dataset, or document
Publisher-controlled reference to the source
AI may assist
Summarize the source
Synthesize multiple sources
Draft or rewrite the passage
Prepare the article for editorial review
AI can assist the production process
External sources remain the evidence for factual claims
Editors still verify claims against the original material
Two layers

Keep generation and evidence separate

AI can summarize, synthesize, draft, rewrite, and reorganize source material. The studies, reports, datasets, documents, and authoritative web sources supporting the resulting factual claims remain the evidence. CiteKit keeps publisher-controlled References to those Sources separate from the generated prose so they can be identified, organized, revisited, and cited.

Publisher-controlled reference layer
AI summarization AI synthesis AI drafting AI rewriting
The problem

The prose can survive while the source trail fragments

AI-assisted synthesis can blend several sources into one polished paragraph, combine sourced facts with model inference, or carry generated citation text forward without the underlying sources being inspected. The publishing problem is not simply whether AI can make mistakes. It is whether an editor can still identify and verify the evidence supporting the claim.

Generated-text workflow

Sources enter AI
Generated prose
Source context becomes unclear

Reference-layer workflow

Record the sources as References
Use AI where appropriate
Verify and cite the originals

From external source to published claim

Use CiteKit as the reference-management layer around AI-assisted production so generated output does not become the only surviving record of the research behind an article.

Find or verify the external source Save it as a Reference in CiteKit Organize the Reference in a Reference Set Use AI where appropriate Review the claim against the original source Publish the Citation, Bibliography, or Source List

Keep the evidence under publisher control

Reusable References

Keep a structured Reference that identifies the external Source instead of leaving its details only inside a prompt, generated draft, browser tab, or citation string.

Article Reference Sets

Group the References used for a particular article in a Reference Set so editors can return to the underlying research during review, correction, or later updates.

Published source connections

Connect source-dependent material to managed References through Citations, Footnotes, Tooltips, Bibliographies, or Source Lists where appropriate.

Generated citation output is not the same as a managed Reference

A generated citation is an output. A managed Reference is the publisher-controlled record that identifies the Source.

Generated citation output is not the same as a managed Reference
Generated citation output Managed Reference
What citation text did the model produce? What Source did the publisher verify and record as a Reference?
20 Sources
  1. 1. Neil Thurman

  2. 2. Sina Thäsler-Kordonouri

  3. 3. Richard Fletcher. AI adoption by UK journalists and their newsrooms: surveying applications, approaches, and attitudes. https://reutersinstitute.politics.ox.ac.uk/ai-adoption-uk-journalists-and-their-newsrooms-surveying-applications-approaches-and-attitudes

  4. 4. AP Corporate Communications. AP updates newsroom standards for artificial intelligence. https://www.ap.org/the-definitive-source/announcements/ap-updates-newsroom-standards-for-artificial-intelligence/

  5. 5. OpenAI. Does ChatGPT tell the truth? https://help.openai.com/en/articles/8313428

  6. 6. Yifei Li

  7. 7. Xiang Yue

  8. 8. Zeyi Liao

  9. 9. Huan Sun. AttributionBench: How Hard is Automatic Attribution Evaluation? https://aclanthology.org/2024.findings-acl.886/

  10. 10. Haolin Deng

  11. 11. Chang Wang

  12. 12. Xin Li

  13. 13. Dezhang Yuan

  14. 14. Junlang Zhan

  15. 15. Tianhua Zhou

  16. 16. Jin Ma

  17. 17. Jun Gao

  18. 18. Ruifeng Xu. WebCiteS: Attributed Query-Focused Summarization on Chinese Web Search Results with Citations. https://aclanthology.org/2024.acl-long.806/

  19. 19. International Committee of Medical Journal Editors. Preparing a Manuscript for Submission to a Medical Journal. https://icmje.org/recommendations/browse/manuscript-preparation/preparing-for-submission.html

  20. 20. MLA Style Center. How do I cite generative AI in MLA style? (Updated and Revised). https://style.mla.org/citing-generative-ai-updated-revised/

Keep important claims traceable to their evidence.

AI can participate in the generation layer. The external Sources supporting important factual claims should remain identifiable through publisher-controlled References that can be revisited for verification, publication, correction, and later review.

Open the Reference Manager