Problem
Two sentences sit next to each other in the same paragraph, in the same voice, with the same confidence. One is drawn from a document the system retrieved a minute ago. The other was produced by a language model with no source behind it. Nothing in the typography distinguishes them.
Solution
Attach the marker to the claim rather than to the answer. That granularity is the entire value of the pattern. A list of eight sources under a response establishes that eight things were consulted and leaves the reader to guess which sentence came from which, or whether any particular sentence came from any of them. A chip at the end of a clause binds one assertion to one source, which is the only form that helps a reader check the assertion they actually doubt.
The common forms are a superscript number, a small pill carrying the source’s favicon, and an underline that reveals a card on hover or focus. The pill carrying a domain is the strongest of the three for general use, because the domain is the fastest trust signal a reader has and it works before any interaction. On interaction, a chip owes the reader four things: the title, the domain, the date of the source, and ideally the passage the claim was drawn from. Date is the most frequently omitted and the most often decisive, since a well-sourced answer built on a page from 2019 is a different object than the same answer built on last month’s.
The honesty problem sits underneath all of this. In a retrieval system the retrieval is real, but the attribution of a particular generated sentence to a particular retrieved chunk is frequently reconstructed after the fact rather than traced. A chip can point at a page that doesn’t contain the claim it’s attached to. That reconstruction is the limit NN/g describes: modern models are complex enough that even the engineers can’t always trace why an output appeared, so an interface that presents attribution as provenance is claiming more than the system knows.
The weakness of that link matters, because a chip earns trust whether or not it’s accurate. A reader who sees citations reads the surrounding prose as verified, and mostly doesn’t click. A decorative citation is therefore worse than no citation, because it converts an unverified claim into one the reader has stopped checking. Any product shipping this pattern owes an evaluation of how often the chip points at a page that supports the sentence.
Density is the last decision. One chip per sentence is unreadable. Clustering at the end of a clause or a sentence, with several chips collapsing into a count once there are more than three, keeps the prose readable.
Use when
The system retrieves from documents or the web and the answer makes checkable factual claims.
Don’t use when
The output is the model’s own composition: a draft, a summary of text the viewer supplied, a rewrite, a piece of code. Citing sources for a generated first draft implies an authority the output doesn’t have.
Trade-offs
Chips interrupt reading rhythm, and the denser the sourcing the worse the prose reads, so accuracy and readability pull against each other directly. They also raise trust faster than they raise verification, which is a net loss if the underlying attribution is weak. Favicons make the source recognisable and turn the answer into a strip of logos. A chip pointing at a paywalled or permission-gated page is worse than no chip at all. The reader can see that verification exists and can’t reach it.
Checklist
- Is the marker attached to a claim or to the whole response?
- How often does the cited page actually support the sentence, and is that measured?
- Does the chip expose the source’s date?
- What does a reader see on hover, on focus, and on a touch device?
- What happens when three sentences in a row share one source?
- Is a paywalled or permission-restricted source marked before the reader clicks?
- Do chips survive copying the answer into another document?
- Can a reader tell which parts of an answer have no source at all?
- Does a dead link fail visibly or silently?
- Are chips reachable and announced in a sensible order by a screen reader?
Compare
Perplexity puts numbered chips inline and resolves the source set before the prose begins, so the citation a sentence points at already exists when the sentence arrives. ChatGPT surfaces sources when a search tool ran and leaves unsourced prose unmarked. A chip means something there, instead of being ambient decoration. Gemini offers a separate verification pass against search rather than treating inline attribution as complete, which concedes that the chip and the check are different operations. Microsoft Copilot inside a tenant cites internal documents, where the hard part is that a cited file may be one the reader has no permission to open.
Related
Source list is the same evidence aggregated, and answers a different question. Reasoning disclosure explains the path rather than the origin. Knowledge cutoff notice covers claims with no source because none was consulted. Tool call trace is the record of the retrieval that produced these sources. Refusal is the alternative when nothing adequate was found.