StressDream: Steering Video World Models
for Robust Policy Evaluation and Improvement
Conference on Robot Learning (CoRL) 2026
Junwon Seo1,
Sushant Veer2,
Ran Tian2,
Wenhao Ding2,
Apoorva Sharma2,
Karen Leung2,3,
Edward Schmerling2,
Marco Pavone2,4,
Andrea Bajcsy1
1 Carnegie Mellon University
2 NVIDIA Research
3 University of Washington
4 Stanford University
We present StressDream, an inference-time method that optimizes diffusion noise to steer video world models toward plausible, high-impact outcomes — enabling robust evaluation and improvement of robotic policies.