arXiv:2610.14289v1 Announce Type: new Abstract: LLM watermarking has emerged as a promising approach for detecting downstream model misuse in centralized settings, but extending it to federated learning (FL) presents unique challenges. In particular, FL systems often rely on strong robust aggregators to defend against poisoning attacks.
Watermarking for Byzantine Robust LLM Training
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