ContextFlow Aligns Task States for Long-Horizon Embodied Agents

A new framework called ContextFlow has been introduced by researchers to tackle the issue of task-state misalignment in long-horizon embodied agents. While specialized executors manage navigation, search, approach, and manipulation, the primary challenge lies in ensuring a consistent task frontier throughout planning, monitoring, memory, and execution. Misalignment occurs when the planner's current stage, runtime evidence, remembered context, and the assigned executor fail to support the same next-step decision, resulting in unsupported transitions, stage lock, executor-context discrepancies, and unnecessary replanning. ContextFlow defines stages as explicit contracts, transforms runtime observations into evidence packets, and implements scoped updates such as continue, refine, transfer, promote, and repair. This framework maintains local closed-loop control by specialist executors while preserving global task coherence. The findings are available on arXiv under ID 2605.19314.