Citations
Citations is an AI UX pattern that attaches verifiable sources to claims in generated answers using inline markers, chips, footnotes, or a source list. Users can inspect where a claim came from without leaving the answer. It is the core trust pattern for research, search, and RAG products.
When to use
Essential for research tools, AI search engines, and knowledge applications where source citations build trust and enable verification of AI claims.
When not to use
- Purely creative or opinionated generation where inventing sources would mislead.
- Offline or closed-corpus tools with no retrievable documents to cite.
- Tiny UI surfaces where chips destroy readability; prefer a single Sources entry instead.
Anti-patterns
- Footnote-only lists that force readers to leave the claim to verify.
- Anonymous numbered markers with no publisher or title identity.
- Citations that open a new tab for every check with no in-product preview.
- Aggregating sources behind +N with no way to inspect each one.
How products use it
| Product | Implementation |
|---|---|
| Perplexity | Domain +N chips inline, research steps, Links tab, and Wrong sources feedback. |
| ChatGPT | Publisher chips, claim popovers with 1/N paging, and a Sources sidebar. |
| Google AI Overviews | Numbered markers in the overview with related source links alongside. |
| Bing Copilot | Inline citations tied to web results in the answer pane. |
Use this pattern in your project
Copy this prompt to generate a production-ready implementation in Cursor, Claude Code, Lovable, or any AI coding agent.
Generate a production-ready implementation of the "Citations" AI interface design pattern.
Pattern Definition:Real-world examples
How shipped products implement citations, from our teardown guides.
Frequently asked questions
What are AI citations in UX?
AI citations are UI affordances that show which sources support a generated claim: inline chips, hover previews, footnotes, or a sources panel. They let users verify answers without treating the model as a black box.
Should citations be inline chips or a sources list?
Use both when possible. Inline chips keep evidence on the claim for skimmers; a Sources sidebar or Links tab supports full audit. Footnote-only lists are weaker for scanning.
How do citations differ from confidence indicators?
Citations point to external evidence. Confidence indicators show the model’s uncertainty. High confidence without sources is still unverifiable; sources without confidence can still be wrong.
When are wrong-source feedback controls worth it?
When sourcing quality is a first-class failure mode—news, finance, health, research. Treating “wrong sources” as feedback taxonomy helps the product improve retrieval, not only answer tone.