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retrieval-guided fine-tuning

topic1 events
papersTODAY 04:00 UTC

Paper Models Retrieval-Guided Fine-Tuning as a Noisy Estimation Problem

A new arXiv paper frames retrieval-guided fine-tuning as a noisy estimation problem, where retrieved documents injected into the training objective introduce statistical uncertainty. The authors derive risk bounds and analyze how architecture choices affect performance under imperfect retrieval. The work aims to give a theoretical grounding for training setups that mix retrieval with fine-tuning.

rag/fine-tuning/theory/research