# SEVI: A Safety Evidence Framework for Real-World Reinforcement Learning

- Source: arXiv cs.RO
- Published: 2026-10-26T04:00:00.000Z
- RoboHot: https://robohot.news/en/items/jzun52i6wy8rsblzkv40tk6jp
- Original: https://arxiv.org/abs/2610.31829

## Summary

The authors propose the SEVI framework, which uses an evidential safety critic to simultaneously estimate future constraint-violation risk and epistemic uncertainty in a single forward pass, judging before an action is executed whether it is unsafe or insufficiently supported by evidence, and overriding that action with an offline-trained recovery policy.