SWAP: Towards Copyright Auditing of Soft Prompts via Sequential Watermarking 事件

SWAP: Towards Copyright Auditing of Soft Prompts via Sequential Watermarking arXiv:2511.04711v2 Announce Type: replace-cross Abstract: Large-scale vision-language models, especially CLIP, have demonstrated remarkable performance across diverse downstream tasks. Soft prompts, as carefully crafted modules that efficiently adapt vision-language models to specific tasks, necessitate effective copyright protection. In this paper, we investigate model copyright protection by auditing whether suspicio