How Do Large Language Models LLMs Decide Which Citations to Include in their responses?
LLMs fan a single prompt into many smaller queries and cite the sources that perform best across all of them. This video explains what that means for getting your brand cited.
Who is this video for?
- Marketers and users who want their content cited in AI answers
- Teams planning content and SEO strategy for GEO
Video content
In this video, you learn:
- Why LLMs expand a prompt into many sub-queries (fan-out)
- Why retrieval (RAG) is what produces a real citation
- How sources are scored on average strength across all sub-queries
- Why consistent coverage can beat a single number-one ranking
- Why deep topical content and strong SEO still drive citations
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