# Feedback World Model Enables Precise Guidance of Diffusion Policy (NeurIPS 2026)

- Source: arXiv cs.RO
- Published: 2026-10-22T04:00:00.000Z
- RoboHot: https://robohot.news/en/items/vdvdtw5auymzanmpyve0iemde
- Original: https://arxiv.org/abs/2605.15705

## Summary

This paper proposes a feedback world model that uses the true states observed after robot execution to perform online closed-loop correction of predictions at inference time, without additional training data or parameter updates. The method can be interpreted as a latent-space observer and provides convergence guarantees under bounded, asymptotically convergent dynamics residuals and a stable feedback gain; it also introduces action-aware guidance to better translate corrected predictions into control.