When World Models Lie: Adaptive Safety Analysis Under Wrong Imaginations.

arXiv:2609.34300v1 Announce Type: cross Abstract: World models offer a powerful substrate for safety reasoning in high-dimensional robotic systems, but they are also fallible: their predictions can be biased, miscalibrated, or confidently wrong. This creates a