Feb. 6, 2024, 5:45 a.m. | Jie Ren Han Xu Pengfei He Yingqian Cui Shenglai Zeng Jiankun Zhang Hongzhi Wen Jiayuan Ding

cs.LG updates on arXiv.org arxiv.org

Generative AI has witnessed rapid advancement in recent years, expanding their capabilities to create synthesized content such as text, images, audio, and code. The high fidelity and authenticity of contents generated by these Deep Generative Models (DGMs) have sparked significant copyright concerns. There have been various legal debates on how to effectively safeguard copyrights in DGMs. This work delves into this issue by providing a comprehensive overview of copyright protection from a technical perspective. We examine from two distinct viewpoints: …

advancement audio authenticity capabilities code concerns contents copyright copyright protection cs.cr cs.lg deep generative models dgms fidelity generated generative generative models images legal perspective protection synthesized technical text

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