New RAG paradigm with iterative retrieval at multiple reasoning steps achieves 15-20% accuracy gain on HotpotQA

Positioned as go-to technique for dynamic, fact-heavy applications with frequently changing information

Research exposed a critical vulnerability where just 5 poisoned documents can corrupt RAG systems.

Clarification article published explaining distinction between RAG and fine-tuning for LLM applications

Proposal of IAT framework for historical user sequence modeling with industrial deployment

Deployment in e-commerce advertising, shopping mall marketing, and live-streaming e-commerce

Publication of a framework moving RAG systems from proof-of-concept to production, outlining anti-patterns and a five-pillar architecture.

Ethan Mollick declared the end of the 'RAG era' as dominant paradigm for AI agents