attention bias 1criticality modeling 1dynamic supervision 1importance sampling 1out-of-distribution robustness 1robotic locomotion 1robot manipulation 1self-evolving learning 1vision-language-action 1visual prediction 1
From the 2 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…
cs.RO2026
DC-WAM: Dynamic-Centric Visual Supervision and Reasoning for World-Action Models
Haoyuan Ji, Lingxiang Fan, Shang Su +4
The paper introduces DC-WAM, a framework that shifts visual supervision in robot world-action models toward dynamic, interaction-relevant features using flow matching and attention…
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…