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MIT's Computer Science and Artificial Intelligence Laboratory found that removing a single training image has little effect on large AI models, a phenomenon called "attribution decay." Researchers Dai and Gifford published the open-access paper in Nature Communications, showing influence fades as datasets scale to 50,000 images.
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