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klotz: retrieval-augmented generation* + llm* + cross-encoders*

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1. How to Use Re-Ranking for Better LLM RAG Retrieval

   In this article, Dr. Leon Eversberg explains how to build an advanced Local Language Model (LLM) Retrieval-Augmented Generation (RAG) pipeline using open-source bi-encoders and cross-encoders for better chatbot performance.

   2024-05-17 Tags: llm, rag, chatbots, bi-encoders, cross-encoders by klotz
2. Open-Source Models, Temperature Scaling, Re-Ranking, and More: Don’t Miss Our Recent LLM Must-Reads

   The Towards Data Science team highlights recent articles on the rise of open-source LLMs, ethical considerations with chatbots, potential manipulation of LLM recommendations, and techniques for temperature scaling and re-ranking in generative AI.

   2024-05-17 Tags: temperature scaling, re-ranking, llm, retrieval-augmented generation, retrieval, bi-encoders, cross-encoders, customer lifetime value, predictive methods, marketers, data scientists, statistical convergence, 19th-century shipwreck, transformer architecture, multi-classifier model, molecular biology, bioinformatics, ai, career transition, physics, data science by klotz

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