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Can Copyright be Reduced to Privacy?
March 26, 2024, 4:44 a.m. | Niva Elkin-Koren, Uri Hacohen, Roi Livni, Shay Moran
cs.LG updates on arXiv.org arxiv.org
Abstract: There is a growing concern that generative AI models will generate outputs closely resembling the copyrighted materials for which they are trained. This worry has intensified as the quality and complexity of generative models have immensely improved, and the availability of extensive datasets containing copyrighted material has expanded. Researchers are actively exploring strategies to mitigate the risk of generating infringing samples, with a recent line of work suggesting to employ techniques such as differential privacy …
abstract ai models arxiv availability complexity copyright cs.cr cs.lg datasets generate generative generative ai models generative models material materials privacy quality researchers type will
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