Coverage (30d)
42vs0
This Week
4vs0
Evidence
1 articlesRelationships
1Timeline
Retrieval-Augmented Generation2026-04-22
Positioned as go-to technique for dynamic, fact-heavy applications with frequently changing information
Retrieval-Augmented Generation2026-04-21
Research exposed a critical vulnerability where just 5 poisoned documents can corrupt RAG systems.
Retrieval-Augmented Generation2026-04-16
Clarification article published explaining distinction between RAG and fine-tuning for LLM applications
Retrieval-Augmented Generation2026-04-06
Publication of a framework moving RAG systems from proof-of-concept to production, outlining anti-patterns and a five-pillar architecture.
Retrieval-Augmented Generation2026-04-03
Ethan Mollick declared the end of the 'RAG era' as dominant paradigm for AI agents
Retrieval-Augmented Generation2026-03-25
Developer shares cautionary tale about RAG system failure at production scale
self-purification2026-03-17
New research explores LLM self-purification mechanisms to defend against data poisoning attacks in RAG systems
Ecosystem
Retrieval-Augmented Generation
useslarge language models6 src
usesFine-Tuning5 src
usesGoogle4 src
usesChunking Strategy1 src
usesContrastive Learning1 src
usesLangChain1 src
self-purification
usesdata poisoning1 src
usesRetrieval-Augmented Generation1 src