criticality modeling 1importance sampling 1robotic locomotion 1self-evolving learning 1vision-language-action 1
From the 1 of 3 linked papers with an AI index.
3 papers
eess.SY2026
Self-Evolving Learning for Embodied AI with Criticality Model
Linxuan He, Yuying Tian, Lingxiang Fan +5
The paper introduces a self‑evolving learning approach for embodied AI that uses a state‑wise criticality model to predict failure and prioritize failure‑prone samples during finet…
eess.SY2026
Towards provable probabilistic safety for scalable embodied AI systems
Linxuan He, Lingxiang Fan, Qing-Shan Jia +13
Embodied AI systems, comprising AI models and physical plants, are increasingly prevalent across various applications. Due to the rarity of system failures, ensuring their safety i…
eess.SY2025
Efficient Safety Verification of Autonomous Vehicles with Neural Network Operator
Lingxiang Fan, Linxuan He, Haoyuan Ji +1
When autonomous vehicles encounter untrained scenarios, ensuring safety hinges on effective safety verification to prevent accidents stemming from unexpected model decisions. Reach…