CAPSafe: A Benchmark for Contextual Action and Plan Safety Reasoning in Embodied Agents
Reasoning about safety is essential for embodied agents powered by large language models (LLMs). We introduce the Contextual Action and Plan Safety benchmark (CAPSafe), designed to evaluate safety reasoning at two levels: (1) an action-level dataset that tests whether a single action is safe given its environmental context, and (2) a plan-level dataset that evaluates whether agents can generate safe long-horizon plans for complex hazardous household tasks. CAPSafe models safety conditions where hazards are situational (inferred from object properties), multiple hazards can co-occur within the same environment, and each is annotated with a relative severity level for fine-grained analysis....
| Authors | Youmna Farag, Svetlana Stoyanchev, Simon Keizer et al. |
|---|---|
| Primary category | cs.RO |
| Published | 20 October 2026 |
| Last updated at source | 20 October 2026 |
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