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Timeline

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

CTRL-RAG2026-03-06

Developed novel reinforcement learning technique to eliminate hallucinations in RAG systems using Contrastive Likelihood Reward.

Ecosystem

CTRL-RAG

usesRetrieval-Augmented Generation1 src

Retrieval-Augmented Generation

useslarge language models6 src
usesFine-Tuning5 src
usesGoogle4 src
usesChunking Strategy1 src
usesContrastive Learning1 src
usesLangChain1 src

Evidence (1 articles)

CTRL-RAG vs Retrieval-Augmented Generation — AI Comparison 2026 | gentic.news