Chain-of-Note (CoN)
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Tencent's Chain-of-Note adds an explicit note-taking step to RAG so the model can evaluate retrieved evidence before answering.
Sequential notes: For each retrieved document, the model writes a "reading note" assessing relevance to the question, rather than attending to the entire retrieval dump directly.
Noise robustness: +7.9 EM improvement when retrieved documents are entirely noisy, precisely the regime where standard RAG degrades most.
Unknown-scenario handling: +10.5 rejection-rate improvement on questions outside the model's training scope, a key property for avoiding confident hallucinations.
Generalizable pattern: The note-taking step is a lightweight addition on top of existing RAG pipelines, making it easy to adopt incrementally.
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