Python代码易暴露，用混淆技巧为算法与商业逻辑穿上“铠甲”
You've built something valuable in Python. Maybe it's a proprietary algorithm, a business logic engine, or an AI application with carefully crafted pr…
一篇针对LLM训练中“数据洗白”问题的检测方案，通过分析模型对专有样本的预测差异来识别数据是否被非法使用
arXiv:2604.01904v2 Announce Type: replace-cross Abstract: Data rights owners can detect unauthorized data use in large language model (LLM) training b…
最新研究提出鲁棒LLM水印方法，在保护知识产权的同时将语义失真降至最低，平衡了安全性与生成质量。
arXiv:2605.23175v1 Announce Type: cross Abstract: Proprietary large language models (LLMs) face risks of intellectual property (IP) violation, as adve…
前沿论文：反蒸馏指纹技术，用于检测LLM被无授权蒸馏，平衡鲁棒性与模型性能。
arXiv:2602.03812v2 Announce Type: replace-cross Abstract: Model distillation enables efficient emulation of frontier large language models (LLMs), cre…