World Models Dream of Success: Diagnosing and Repairing Failure Insensitivity in Robot World Models

arXiv:2610.09134 · cs.RO · Submitted 2026-10-06 · Read on arXiv

cs.RO

Submitted: 2026-10-06

Updated: 2026-10-06

Code: https://github.com/jiuyixu25/CureWM

Terminology

• AUROC — 25× in this paper · explained in 2 episodes
• World Model — 22× in this paper · explained in 7 episodes
• Adaptation — 15× in this paper · explained in 1 episode
• Fine-Tuning — 6× in this paper · explained in 5 episodes
• Accuracy — 5× in this paper · explained in 1 episode
• Ablation — 3× in this paper · explained in 1 episode
• Benchmark — 3× in this paper · explained in 2 episodes
• Consistency — 3× in this paper · explained in 3 episodes
• Fidelity — 3× in this paper · explained in 2 episodes
• Reinforcement Learning — 3× in this paper · explained in 4 episodes
• Verification — 3× in this paper · explained in 2 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Hallucination — 2× in this paper · explained in 3 episodes
• Action Flow — 1× in this paper · explained in 1 episode
• Action-Conditioned World Model — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Deep Reinforcement Learning — 1× in this paper · explained in 2 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Diffusion Models — 1× in this paper · explained in 6 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Latent World Models — 1× in this paper · explained in 2 episodes
• Point Clouds — 1× in this paper · explained in 2 episodes
• Q-learning — 1× in this paper · explained in 3 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Synthetic Data Generation — 1× in this paper · explained in 5 episodes

Sources

• Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets
• AgiBot World Colosseo: A Large-scale Manipulation Platform for Scalable and Intelligent Embodied Systems
• AEGIS: A Backup Reflex for Physical AI
• Ctrl-World: A Controllable Generative World Model for Robot Manipulation
• World Models
• Hallucination in World Models is Predictable and Preventable
• RoboWM-Bench: A Benchmark for Evaluating World Models in Robotic Manipulation
• Learning Actionable Manipulation Recovery via Counterfactual Failure Synthesis
• Cosmos World Foundation Model Platform for Physical AI
• GR00T N1: An Open Foundation Model for Generalist Humanoid Robots
• FACT: Failure-Aware Causal Training for World-Action Models
• Is the Future Compatible? Diagnosing Dynamic Consistency in World Action Models
• WorldArena: A Unified Benchmark for Evaluating Perception and Functional Utility of Embodied World Models
• MiraBench: Evaluating Action-Conditioned Reliability in Robotic World Models
• Foresight: Failure Detection for Long-Horizon Robotic Manipulation with Action-Conditioned World Model Latents

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