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News/Collaborative Threshold Watermarking
arxiv
PublishedMay 29, 2026 at 4:00 AM
—neutral

Collaborative Threshold Watermarking

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Publisher summary· verbatim

arXiv:2602.10765v2 Announce Type: replace Abstract: In federated learning (FL), $K$ clients jointly train a model without sharing raw data. Because each participant invests data and compute, clients need mechanisms to later prove the provenance of a jointly trained model. Model watermarking embeds a

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