This result is particularly interesting for capabilities that are harder for models (like numerical reasoning or text rendering) as prompt-aware guidance boosts performance on these failure modes without retraining.

Most diffusion-based models use a fixed (model-tuned) guidance schedule. We show that picking the guidance value during inference, conditioned on the prompt/capability, significantly improves performance.

arxiv.org/abs/2509.16131

We design 3 main tasks with varying degrees of difficulty and evaluate 13 models across different families. Models show rudimentary numerical reasoning skills, limited to small numbers and simple prompt formats; many models are affected by non-numerical prompt manipulations.