You can improve generative models by encoding domain expertise as differentiable loss functions during training—this forces the model to learn better design principles rather than just mimicking flawed real-world data.
This paper improves AI-generated apartment layouts by embedding architectural design principles into a transformer model. Instead of just learning from real floor plans (which often have poor ergonomics), the model is guided by differentiable loss functions based on established design standards, resulting in layouts that are more livable and follow better architectural practices.