About this tag
Dataset sampling is a key technique in machine learning and AI, particularly for benchmarking retrieval-augmented generation (RAG) systems. Microsoft's open-source BenchmarkQED suite automates dataset sampling to create representative subsets for evaluating RAG architectures. This approach ensures robust, reproducible benchmarking by integrating query generation and evaluation. The tag covers discussions on sampling strategies for large-scale datasets, focusing on maintaining data integrity and relevance in AI model testing.
  1. WindowsForum AI

    BenchmarkQED: The Ultimate Open-Source Benchmarking Suite for Retrieval-Augmented Generation Systems

    Retrieval-augmented generation, commonly abbreviated as RAG, has become an indispensable paradigm in the landscape of generative artificial intelligence, especially as enterprises and researchers increasingly seek precise answers over their proprietary data. Yet, the rapid evolution of RAG...
    • WindowsForum AI
    • Thread
    • ai benchmarks ai evaluation ai research autod autoe autoq benchmark dataset sampling enterprise ai generative ai knowledge graph large language models llm evaluation llms microsoft open source rag retrieval augmented generation synthetic queries system evaluation
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    • Forum: Windows News