InCubedbyMichael WoodThe Insanity of Relying on Vector Embeddings: Why RAG FailsIn RAG, the goal is to locate the stored information that has the highest percentage of sameness to the provided query. Vector similarity…Nov 21, 202466Nov 21, 202466
Florian JuneAn Innovative RAG Idea for Multi-hop Question AnsweringIn open-domain question answering, multi-hop question answering is complex and challenging. It requires the system to integrate information…Sep 6, 2024Sep 6, 2024
InTDS ArchivebyThuwarakesh Murallie5 Proven Query Translation Techniques To Boost Your RAG PerformanceHow to get near-perfect LLM performance even with ambiguous user inputsAug 8, 20246Aug 8, 20246
InTDS ArchivebyDominik Polzer17 (Advanced) RAG Techniques to Turn Your LLM App Prototype into a Production-Ready SolutionA collection of RAG techniques to help you develop your RAG app into something robust that will lastJun 26, 202430Jun 26, 202430
InThe AI ForumbyPlaban NayakRAG on Complex PDF using LlamaParse, Langchain and GroqRetrieval-Augmented Generation (RAG) is a new approach that leverages Large Language Models (LLMs) to automate knowledge search, synthesis…Apr 7, 202412Apr 7, 202412
InTDS ArchivebyYouness MansarClone the Abilities of Powerful LLMs into Small Local Models Using Knowledge DistillationBoost the performance of local LLMs using supervision from larger onesApr 2, 20243Apr 2, 20243
khalid bouzianeHarnessing RAG for Text, Tables, and Images: A Comprehensive GuideIn the realm of information retrieval, Retrieval Augmented Generation (RAG) has emerged as a powerful tool for extracting knowledge from…Nov 28, 20231Nov 28, 20231