RAG in in-context linear regression has an exact bias-variance tradeoff and a finite-sample bound revealing a generalization ceiling as retrieved examples grow.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Retrieval-Augmented Generation as Noisy In-Context Learning: A Unified Theory and Risk Bounds
RAG in in-context linear regression has an exact bias-variance tradeoff and a finite-sample bound revealing a generalization ceiling as retrieved examples grow.