Explainability-in-Action: Enabling Expressive Manipulation and Tacit Understanding by Bending Diffusion Models in ComfyUI
Abuzuraiq, Ahmed M., Pasquier, Philippe
–arXiv.org Artificial Intelligence
Explainable AI (XAI) in creative contexts can go beyond transparency to support artistic engagement, modifiability, and sustained practice. While curated datasets and training human-scale models can offer artists greater agency and control, large-scale generative models like text-to-image diffusion systems often obscure these possibilities. We suggest that even large models can be treated as creative materials if their internal structure is exposed and manipulable. We propose a craft-based approach to explainability rooted in long-term, hands-on engagement akin to Schön's "reflection-in-action" and demonstrate its application through a model-bending and inspection plugin integrated into the node-based interface of ComfyUI. We demonstrate that by interactively manipulating different parts of a generative model, artists can develop an intuition about how each component influences the output.
arXiv.org Artificial Intelligence
Aug-12-2025
- Country:
- Asia > Japan
- Honshū > Kantō > Kanagawa Prefecture > Yokohama (0.04)
- Europe > Portugal
- North America
- Canada > British Columbia
- Metro Vancouver Regional District > Surrey (0.05)
- United States
- Hawaii (0.04)
- New York > New York County
- New York City (0.05)
- Canada > British Columbia
- Asia > Japan
- Genre:
- Research Report (0.40)
- Technology: