RAG is the most widely deployed LLM pattern outside chatbots. New work advances retrievers (ColBERT, SPLADE, hybrid), long-context handling, and production evaluation. Relaylit surfaces the research that's actually useful to people building RAG in production.
Retrieval-augmented generation
Hybrid retrievers, late interaction, evaluation, long-context.
Example brief
Where Relaylit searches for this topic
How Relaylit tracks retrieval-augmented generation
1. Describe it once
Paste a plain-language brief for retrieval-augmented generation. No boolean operators, no saved-search syntax.
2. We search 2 databases
Relaylit queries arXiv and Semantic Scholar on the live APIs, deduplicates the results, and ranks each paper against your brief.
3. Read the digest
A focused, ranked email lands weekly, biweekly, or monthly — the strongest retrieval-augmented generation work, not a raw feed.
Frequently asked questions
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