RAG, Fine-Tuning & ContextZhuowan Li et al. (Google DeepMind, University of Michigan)Google DeepMind
Retrieval Augmented Generation or Long-Context LLMs? published
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Retrieval Augmented Generation or Long-Context LLMs? published — compares the two approaches and proposes a hybrid that routes based on the model's self-assessment
Why it matters
Framed the long-context vs RAG debate as a cost-performance trade-off
Source — Primary sources first; secondary reports are labelled “Press”
Paperarxiv.orghttps://arxiv.org/abs/2407.16833Added in Week 35, 2026 · See that week
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