ContextFlow: Hierarchical Task-State Alignment for Long-Horizon Embodied Agents
Long-horizon embodied agents increasingly delegate navigation, search, approach, and manipulation to specialist executors. As these executors become stronger, the main bottleneck shifts from local skill execution to maintaining a coherent task frontier across planning, monitoring, memory, and execution. We study task-state misalignment, a task-level consistency failure in which the planner's active stage, runtime evidence, remembered context, and delegated executor no longer justify the same nex
Record details
Published: 19 May 2026
Source: arXiv
Category: Research
Topics: Safety & alignment · Agents & autonomy
Retrieved: 14 July 2026
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ethics.ai (19 May 2026), “ContextFlow: Hierarchical Task-State Alignment for Long-Horizon Embodied Agents,” evidence record 4060, https://ethics.ai/record/4060 (originally published by arXiv).
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