Safe at the Finish, Unsafe on the Way: What SafeRelBench Exposes in Embodied AI
TL;DR for operators A manipulation agent can reach the requested final state and still have executed the task unsafely. That creates a measurement problem for teams using task-completion rates to decide whether an embodied model, prompt, or policy update is ready for deployment. SafeRelBench tests this gap directly. Across seven evaluated VLM-driven agents, the spatial-relation cases produced task Success Rates (SR) of 0.52–0.73 but Safety Success Rates (SSR) of only 0.16–0.40. In matched non-spatial settings, SR rose to 0.83–0.94 and SSR reached as high as 0.91.1 The benchmark therefore measures something final-state success can miss: whether the agent satisfied the relevant safety prerequisite before taking the risky action. ...