A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
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This paper presents methods, metrics, and comparisons for uncertainty quantification in scientific machine learning, along with an open-source Python library.
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This paper provides a comprehensive analysis of when to use graphs in retrieval-augmented generation, offering a decision framework and empirical comparisons of GraphRAG versus vector RAG.
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A comprehensive survey of Small Language Models (SLMs) covering architectures, training methods, and model comparisons.