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CAPSafe benchmark evaluates safety reasoning for actions and long-horizon planning in embodied agents

Researchers propose the CAPSafe benchmark, which evaluates the safety reasoning capabilities of large language model-driven embodied agents at two levels: an action-level dataset that judges whether a single action is safe in a given environmental context, and a plan-level dataset that assesses whether agents can generate safe long-horizon plans for complex hazardous household tasks.

Part of the event: CAPSafe Benchmark Evaluates Safety Reasoning Capabilities of Embodied Agents

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