Diffusion Integrated Gradients: Controllable Path Generation for Flexible Feature Attribution
Researchers introduce Diffusion Integrated Gradients (DiffIG), a novel explainable AI method that uses diffusion models to generate optimized attribution paths instead of relying on fixed hand-crafted paths. The approach enables inference-time controllable feature attribution with improved explanation quality and perceptual alignment compared to existing path-based methods.