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2026-05-09 17:24:46 -04:00
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# Citation Sentinel # Citation Sentinel
A source-grounded research assistant that employs cosine similarity scoring for LLM generated query responses to provide a "groundedness" score. This is a metric in Retrieval-Augmented Generation (RAG) systems that quantifies how well an AI-generated answer is supported by retrieved context. It measures "faithfulness" to source documents, ensuring the answer is not hallucinated or pulled from the model's pre-training data. A source-grounded research assistant that employs cosine similarity scoring for LLM-generated query responses to provide a "groundedness" score. This is a metric in Retrieval-Augmented Generation (RAG) systems that quantifies how well an AI-generated answer is supported by retrieved context. It measures "faithfulness" to source documents, ensuring the answer is not hallucinated or pulled from the model's pre-training data.
Users upload source documents, or provide links to online sources including audio/video (i.e. links to youtube videos). Users may then ask questions and receive answers (with inline citations) verifiably grounded in the provided information sources. Users upload source documents, or provide links to online sources including audio/video (i.e. links to youtube videos). Users may then ask questions and receive answers (with inline citations) verifiably grounded in the provided information sources.