Plan First, Diffuse Later: Extrinsic Graph Guidance for Long-Horizon Diffusion Planning

1. 1Build a compositional diffusion model to denoise multiple overlapping sub-trajectories
2. 2Apply extrinsic graph guidance to enforce local behavior and global structure coherence
3. 3Configure the model to explore multiple paths during the denoising process
4. 4Test the model on long-horizon planning tasks to evaluate its performance
5. 5Refine the model by adjusting parameters and exploring different graph guidance techniques

AI engineers and researchers on a team can benefit from this knowledge to develop more effective planning models, while data scientists can apply these concepts to real-world problems

💡 Extrinsic graph guidance can enhance the coherence of global structures in compositional diffusion models

💡 Improve long-horizon planning with extrinsic graph guidance for compositional diffusion models!