graph-world-models

This paper introduces GAVEL, a framework that uses graph world models to verify and repair long-horizon LLM planning for robotic tasks, significantly improving success rates and efficiency in simulations.

This paper analyzes long-horizon rollout error in Graph World Models (GWMs), proposing a unified framework with dynamic edges and introducing Error-Aware GWM that uses spectral regularization, rollout consistency, and critical-node weighting to prevent divergence.