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Data-Centric Artificial Intelligence

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arxiv 2212.11854 v4 pith:LYOSLDLO submitted 2022-12-22 cs.AI

classification cs.AI
keywords data-centricartificialintelligenceintroduceparadigmsystemsai-basedarticle
verification ladder T0 review T1 audit T2 compute T3 formal
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Data-centric artificial intelligence (data-centric AI) represents an emerging paradigm emphasizing that the systematic design and engineering of data is essential for building effective and efficient AI-based systems. The objective of this article is to introduce practitioners and researchers from the field of Information Systems (IS) to data-centric AI. We define relevant terms, provide key characteristics to contrast the data-centric paradigm to the model-centric one, and introduce a framework for data-centric AI. We distinguish data-centric AI from related concepts and discuss its longer-term implications for the IS community.

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Cited by 1 Pith paper

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  1. Out-of-distribution data supervision towards biomedical semantic segmentation

    cs.CV 2025-07 reject novelty 4.0 of 10

    Med-OoD adds background-only 'OOD' patches from the ID dataset as negative samples with zero-mask Dice loss, claiming modest gains on Lizard but an internally inconsistent 76.1% mIoU for the OOD-only case.

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