9 papers
Margin-Drop Coordinates for Cross-Budget Robustness Evaluation
Yanliang Huang, Zhen Zhang, Peng Xie +4
Fixed-budget robustness evaluation can select the wrong frozen vision encoder. An encoder that survives a shallow attack may lose most of that robustness when the same evaluation i…
Probabilistic Reachable-Action Verification of Visuomotor Policies via Set-Based Training
Yanliang Huang, Zhuocheng Zhang, Peng Xie +5
Reachability analysis for visuomotor policies is difficult because large visual encoders make end-to-end set propagation computationally expensive and excessively conservative. We…
Certifying Plans under Model Mismatch: A Trilemma for Reachability from Scarce Data
Yanliang Huang, Zhen Zhang, Ahmad Hafez +4
Sim-to-real policies are designed under nominal dynamics, but target-system trials may yield only a few isolated one-step transitions. We study pre-execution certification of a fix…
Certified Set Convergence for Piecewise Affine Systems via Neural Lyapunov Functions
Yanliang Huang, Peng Xie, Zhen Zhang +3
Safety-critical control of piecewise affine (PWA) systems under bounded additive disturbances requires guarantees not for individual states but for entire state sets simultaneously…
Data-Driven Reachability Analysis via Diffusion Models with PAC Guarantees
Yanliang Huang, Peng Xie, Wenyuan Wu +2
We present a data-driven framework for reachability analysis of nonlinear dynamical systems that requires no explicit model. A denoising diffusion probabilistic model learns the ti…
Conformalized Data-Driven Reachability Analysis with PAC Guarantees
Yanliang Huang, Zhen Zhang, Peng Xie +2
Data-driven reachability analysis computes reachable sets directly from noisy data. Existing matrix-zonotope reachability methods require a known noise bound, and their nonlinear e…
Bi-LSTM based Multi-Agent DRL with Computation-aware Pruning for Agent Twins Migration in Vehicular Embodied AI Networks
Yuxiang Wei, Zhuoqi Zeng, Yue Zhong +3
With the advancement of large language models and embodied Artificial Intelligence (AI) in the intelligent transportation scenarios, the combination of them in intelligent transpor…
TinyMA-IEI-PPO: Exploration Incentive-Driven Multi-Agent DRL with Self-Adaptive Pruning for Vehicular Embodied AI Agent Twins Migration
Zhuoqi Zeng, Yuxiang Wei, Jiawen Kang
Embodied Artificial Intelligence (EAI) addresses autonomous driving challenges in Vehicular Embodied AI Networks (VEANETs) through multi-modal perception, adaptive decision-making,…
Predictive Traffic Rule Compliance using Reinforcement Learning
Yanliang Huang, Sebastian Mair, Zhuoqi Zeng +1
Autonomous vehicle path planning has reached a stage where safety and regulatory compliance are crucial. This paper presents an approach that integrates a motion planner with a dee…