Retrieval-augmented generation
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The setting for Glance: retrieved passages are reranked and used by a generator to answer, where separate reranking and answering models normally duplicate model residency and passage processing.
Grounds a language model's output in retrieved evidence.
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- Mapping the RAG Landscape: A Four Axis Taxonomy of Efficiency, Defense, Interactivity, and Reasoning
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Discussed as a target: planted vector metadata can manipulate RAG output, as in a clinical RAG case that produced a dangerous dose recommendation.
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