AI RESEARCH
Functional Subspace Watermarking for Large Language Models
arXiv CS.AI
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ArXi:2603.18793v1 Announce Type: cross Model watermarking utilizes internal representations to protect the ownership of large language models (LLMs). However, these features inevitably undergo complex distortions during realistic model modifications such as fine-tuning, quantization, or knowledge distillation, making reliable extraction extremely challenging. Despite extensive research on model-side watermarking, existing methods still lack sufficient robustness against parameter-level perturbations.