Emerging Trends and Research in RAG
Stay updated on the latest advancements, research papers, and future directions in Retrieval Augmented Generation and LLM integration.
Beyond Basic RAG
RAG is evolving fast! We've covered the basics, but researchers are constantly pushing boundaries. This lesson explores exciting new trends, from self-correcting models to multi-modal data.
Self-Correction & Self-RAG
A major trend is enabling LLMs to critique and improve their own work. Self-correction means the LLM can identify flaws in its generated answer or retrieved documents and try again.
- Self-RAG is a framework where the LLM decides when to retrieve, generates an answer, and then critically evaluates both the retrieved info and its own response.
- It can trigger further retrieval or regeneration steps if confidence is low.
All lessons in this course
- RAG for Code Generation and Assistance
- Building Real-time RAG Systems
- Emerging Trends and Research in RAG
- Multimodal RAG with Images and Tables