We present EKILA; a decentralized framework that enables creatives to receive
recognition and reward for their contributions to generative AI (GenAI). EKILA
proposes a robust visual attribution technique and combines this with an
emerging content provenance standard (C2PA) to address the problem of synthetic
image provenance -- determining the generative model and training data
responsible for an AI-generated image. Furthermore, EKILA extends the
non-fungible token (NFT) ecosystem to introduce a tokenized representation for
rights, enabling a triangular relationship between the asset's Ownership,
Rights, and Attribution (ORA). Leveraging the ORA relationship enables creators
to express agency over training consent and, through our attribution model, to
receive apportioned credit, including royalty payments for the use of their
assets in GenAI.

EKILA 是一个分散化的框架，结合视觉归属技术和内容出处标准解决合成图像的来源问题，同时通过引入非替代通证生态系统来赋予训练内容的使用所有权、官网授权和归属表示的能力，使得图片的创作者可以授权到图片被应用到 GenAI 中所得到的收益。