为艺术家定制AI创作工具，保持风格一致性且保护隐私。
BLK-Assist: A Methodological Framework for Artist-Led Co-Creation with Generative AI Models
- 用参数高效方法微调扩散模型，适配特定艺术家风格。
- 生成高分辨率图像时保留透明度与纹理细节，效果优于传统方法。
- 框架可复现、可迁移，适合注重版权与创作主权的艺术家。
本文提出BLK-Assist，一个面向艺术家定制的生成式AI协作框架，采用参数高效微调技术对扩散模型进行个性化优化。系统包含三个模块：基于LoRA的BLK-Conceptor用于概念草图生成；基于LayerDiffuse的BLK-Stencil实现透明度保留的资产生成；以及结合Real-ESRGAN与纹理条件扩散的BLK-Upscale，用于高分辨率输出。通过公开模型与流程文档，展示了一种在保护隐私、尊重授权前提下，实现风格忠实、可复现的人机共创方案，适用于其他艺术家在类似约束下的应用。
原文摘要 · Abstract (English)
This paper presents BLK-Assist, a modular framework for artist-specific fine-tuning of diffusion models using parameter-efficient methods. The system is implemented as a case study with a single professional artist's proprietary corpus and consists of three components: BLK-Conceptor (LoRA-adapted conceptual sketch generation), BLK-Stencil (LayerDiffuse-based transparency-preserving asset generation), and BLK-Upscale (hybrid Real-ESRGAN and texture-conditioned diffusion for high-resolution outputs). We document dataset composition, preprocessing, training configurations, and inference workflows to enable reproducibility with publicly available models to illustrate a privacy-preserving, consent-based approach to human-AI co-creation that maintains stylistic fidelity to the source corpus and can be adapted for other artists under similar constraints.
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