Advance RAG 05 - Merger Retriever and LongContextReorder | Lost in Middle Phenomenon

In this video, we dive deep into advanced Retrieval-Augmented Generation (RAG) techniques, specifically focusing on the Merger Retriever and LongContextReorder methods. We explore how these techniques can effectively tackle the "Lost in Middle Phenomenon," a common challenge in information retrieval systems where critical information gets buried in the middle of long contexts. By merging retrievers and optimizing context ordering, we can significantly enhance the performance and accuracy of RAG systems. Whether you're a data scientist, AI enthusiast, or a developer working with RAG models, this video provides valuable insights and practical strategies to improve your systems.

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Downlaod the Notes From Here: github.com/sunnysavita10/Generative-AI-Indepth-Bas…
Notebook Link: github.com/sunnysavita10/Generative-AI-Indepth-Bas…
Research paper Link: arxiv.org/abs/2307.03172
Download model from here: huggingface.co/TheBloke/zephyr-7B-beta-GGUF/blob/m…
Langchain Context Compression: python.langchain.com/v0.1/docs/modules/data_connec…

Multimodel RAG Playlis:    • Multimodal RAG Systems: Comprehensive Intr...  
RAG detailed Playlist:    • End to End RAG Pipeline Part-1 | RAG Archi...  
GenAI Foundation Playlist:    • DAY - 1 | Introduction to Generative AI Co...  

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