Tri-Info: Generalizable, Interpretable Failure Prediction for VLA Models via Information Theory
Vision-Language-Action (VLA) models are increasingly deployed across diverse tasks, yet they remain black boxes whose physical interactions can cause irreversible harm, making generalizable and interpretable failure detection essential. We observe that successful and failed rollouts carry systematically different information-theoretic signatures. Building on this, we formalize VLA control as a closed-loop information pipeline and derive the Triple Information-theoretic (Tri-Info) signals that capture whether actions remain diverse, temporally consistent, and coupled to state transitions. Across six VLA models and three benchmark environments, Tri-Info matches the strongest baselines in-do...
| Authors | Jinghan Yang, Yunchao Zhang, Wang Yuan et al. |
|---|---|
| Primary category | cs.RO |
| Published | 18 June 2026 |
| Last updated at source | 30 September 2026 |
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