3 papers
eess.SY2026
Self-Evolving Learning for Embodied AI with Criticality Model
Linxuan He, Yuying Tian, Lingxiang Fan +5
Despite rapid advances in policy pretraining, embodied AI systems routinely plateau during task-specific finetuning. The root cause lies in how finetuning data are collected: the d…
cs.RO2026
DC-WAM: Dynamic-Centric Visual Supervision and Reasoning for World-Action Models
Haoyuan Ji, Lingxiang Fan, Shang Su +4
World-Action Models (WAMs) augment robot policies with future visual prediction, but it remains unclear what the visual modality should learn for control. While photorealistic futu…
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…