All terms
The 2026 vocabulary of Generative Engine Optimization, with live per-term citation status across ChatGPT, Perplexity, Claude, and Copilot.
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A
intermediate
Agentic retrieval
Agentic retrieval is a search pattern where an AI agent autonomously decides what to query, when to query again, and which sources to consult. It replaces single-shot keyword retrieval with iterative, goal-directed information gathering.
GPT·Plx·Cld0×Cop0×Gem0×intermediate
Authoritative Statement Strength
Authoritative statement strength is widely recommended in SEO content as a citation lever. Aggarwal et al. 2023's GEO paper tested 'Authoritative' tone as one of nine content-modification methods and reported verbatim 'to the contrary we find no significant improvement', a null finding rather than a modest lift. The +10% relative gain in raw PAWC numbers (21.3 vs baseline 19.3) was not framed by the paper as statistically meaningful. The folk wisdom that authoritative tone is a primary AI-citation lever has no empirical support in the only public benchmark; it is paper-verbatim null.
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C
advanced
C-SEO Bench
C-SEO Bench is the Puerto et al. 2025 NeurIPS Datasets & Benchmarks paper that evaluates 9 Conversational Search Engine Optimization methods across 6 domains, two tasks (question answering + product recommendation), and continuous multi-actor adoption rates. Its headline finding is that most current C-SEO methods are largely ineffective once tested outside the single-actor synthetic conditions of prior GEO benchmarks; a traditional retrieval-ranking SEO baseline (moving the source to context position 1) is roughly 7.6× more effective in their retail-domain measurement than the best C-SEO method tested.
GPT0×Plx·Cld0×Cop0×Gem·intermediate
Citation match rate
Citation match rate is the percentage of AI-engine references to a source that include a clickable link back to that source. Computed as (linked citations) ÷ (all attributed references) × 100, it isolates the link-bearing subset of attribution from unlinked mentions in the same response stream.
GPT·Plx·Cld·Cop·Gem·advanced
Citation precision and recall
Citation precision is the fraction of citations in an AI engine's response that actually support the sentence they are attached to. Citation recall is the fraction of generated sentences that are fully supported by their citations. Both are model-behavior metrics, not publisher-visibility metrics: they measure how faithfully an AI engine uses the sources it cites, not how often a publisher's content appears as a source.
GPT·Plx·Cld0×Cop0×Gem·intermediate
Citation probe protocol
A citation probe protocol is the standardized operating procedure for measuring whether AI engines cite a publisher's content. It locks down query design, cadence, engine coverage, recording schema, disambiguation rules, and signal-vs-noise thresholds, turning ad-hoc 'ask ChatGPT and see' into a repeatable, comparable, vendor-neutral measurement program. Practitioner-coined methodology entry; the cluster's foundational SOP for the six citation-metrics anchors.
GPTPlx·CldCopGem·intermediate
Cite Sources Optimization
Cite Sources Optimization is one of the four top-performing source-content modification methods in Aggarwal et al. 2023's GEO paper. The method actively rewrites content to add inline source citations for claims made, scoring PAWC 24.6 vs baseline 19.3 (~27% relative gain). The practitioner discipline framing extends the paper's one-shot intervention into a habitual writing technique.
GPT0×Plx·Cld·Cop0×Gem0×intermediate
Cite-ability
Cite-ability is a practitioner-coined content property describing how suitable a passage is for AI extraction, quotation, and attribution. It is informed by factors like structural clarity, self-contained phrasing, and attribution clarity, but it is not a formal industry metric and is not defined in any major academic paper.
GPT·Plx·Cld·Cop0×Gem0×intermediate
Claude citation
Claude citations are the source attributions Anthropic's Claude produces when its web search tool returns real-time web content for grounding. Citations appear inline as source chips in consumer surfaces (claude.ai web app, mobile, Claude Desktop) and as structured web_search_result_location fields in the Anthropic API response. Distinct measurement target from Perplexity, Microsoft Copilot, AI Overview, and AI Mode.
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D
intermediate
DefinedTerm schema
DefinedTerm is a schema.org type representing a term defined elsewhere (typically in a glossary), helping systems that parse structured data understand a term, its definition, and its relationship to a glossary source.
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DuckDuckGo AI citation
DuckDuckGo AI citation is the discrete event of a webpage being included as a linked source in DuckDuckGo's AI surfaces. Two surfaces matter: Search Assist (the AI-generated inline answer above DuckDuckGo search results, formerly DuckAssist, which always links to one or two sources beneath the summary) and Duck.ai (the privacy-anonymized chat interface to third-party models, where citation behavior depends on the underlying model). DuckDuckGo runs its own crawler, DuckAssistBot, for Search Assist.
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E
F
H
P
Q
S
intermediate
Sub-document retrieval
Sub-document retrieval is the practice of indexing and retrieving passages or paragraphs rather than whole documents. It is a common retrieval pattern in RAG and AI-search systems, especially when long documents need to be matched against specific user queries.
GPTPlx·CldCopGemintermediate
Sub-passage extraction
Sub-passage extraction is a practitioner shorthand for the content-level phenomenon of answer systems quoting a single sentence- or claim-level fragment from a retrieved passage. In classical IR the same operation is called extractive QA or span selection; this entry uses 'sub-passage extraction' to align with the 'sub-document retrieval' framing and to cover both classical and LLM-era behavior under one term.
GPT·Plx·Cld0×Cop·Gem·intermediate
Sycophancy vs cite-able fact
Sycophancy is the LLM failure mode of producing agreeable, hedge-laden, or context-flattering responses at the expense of factual specificity. Cite-able fact production is a separate content-writing pattern that emphasizes specific, attributed, falsifiable claims. The two are not strict opposites, but understanding both is useful for AI-search content writers.
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