Large language models do not scan the entire web to answer questions; instead, they rely on a multi-stage pipeline for citation. This process begins with query interpretation, where a user's request is broken down into subqueries. These subqueries are then used for retrieval, where an index or corpus is searched for relevant documents. Retrieved documents are chunked and reranked to select the most pertinent passages, which are then used by the generator to craft an answer. Finally, citations are aligned with the generated claims and presented to the user. AI
IMPACT Understanding LLM citation mechanisms is crucial for developers to improve answer grounding and user trust.
RANK_REASON The item explains a technical process of LLMs rather than announcing a new product or research breakthrough.
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