arXiv:2509. 03122v4 Announce Type: replace-cross Abstract: Reliable model fingerprints are essential for protecting large language models (LLMs) against unauthorized redistribution and commercial misuse.
By Yue Li, Xin Yi, Dongsheng Shi, Yongyi Cui, Gerard de Melo, Linlin Wang
arXiv:2607. 25633v1 Announce Type: cross Abstract: Large language models (LLMs) are costly intellectual assets that remain exposed to unauthorized redistribution and commercial misuse.
By Yongyi Cui, Yue Li, Tianbao Jiang, Xin Yi
arXiv:2505. 12682v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly released under restricted licenses, creating a growing need for robust model ownership verification.
By Yun-Yun Tsai, Jia Hao Liang, Chuan Guo, Junfeng Yang, Laurens van der Maaten
arXiv:2607. 14113v1 Announce Type: cross Abstract: While many AI-generated text (AIGT) detectors achieve strong performance on clean inputs, their accuracy degrades significantly under light paraphrasing, word substitutions, character edits, and distribution shifts.
By Gayan K. Kulatilleke, Mahsa Baktashmotlagh, Siamak Layeghy, Marius Portmann
arXiv:2609.24084v1 Announce Type: cross
Abstract: Open-weight large language models (LLMs) can be copied, modified, and redeployed behind black-box APIs, making post-release ownership verification di...
By Jiaxin Hong, Yuxin Peng, Hongyao Yu, Hao Fang, Shuoyang Sun, Bin Chen
arXiv:2512. 05518v2 Announce Type: replace-cross Abstract: Open-source Large Language Models (LLMs) play a critical role in the democratization of AI, yet their "open" nature introduces more avenues for malicious actors to misuse them for harmful purposes.
By Jason Vega, Gagandeep Singh