In the news
Cited but Unused: Parametric Provenance in Retrieval-Augmented Generation
arXiv cs.AI · Published · 3 min read
In 30 seconds
- What happened
- Researchers found that retrieval-augmented generation systems cite sources for claims they actually derive from internal model memory, not retrieved context.
- Why it matters
- Engineers building or evaluating RAG systems need to understand that citations may be misleading and standard verification methods fail to catch this problem.
- Watch out
- The detection method developed measures what models know rather than what they actually used, leaving the core problem of separating knowledge from usage unsolved.
- retrieval
- eval
The patterns behind this
Each one covers how the technique works, when it earns its cost, and where it breaks.
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