5 papers
VLAMotor: Test-Guided Enhancement of Vision-Language-Action Models via Agent-BasedData Synthesis
Zeqin Liao, Peifan Ren, Zixu Gao +6
Vision-Language-Action (VLA) models follow a data-driven paradigm and are constrained by the coverage of training data, making them prone to failure on edge-case configurations aft…
Detecting Non-Optimal Decisions of Embodied Agents via Diversity-Guided Metamorphic Testing
Wenzhao Wu, Yahui Tang, Mingfei Cheng +3
As embodied agents advance toward real-world deployment, ensuring optimal decisions becomes critical for resource-constrained applications. Current evaluation methods focus primari…
Semantic Intelligence: A Bio-Inspired Cognitive Framework for Embodied Agents
Wenbing Tang, Meilin Zhu, Fenghua Wu +1
Recent advancements in Large Language Models (LLMs) have greatly enhanced natural language understanding and content generation. However, these models primarily operate in disembod…
Causality-aware Safety Testing for Autonomous Driving Systems
Wenbing Tang, Mingfei Cheng, Renzhi Wang +4
Simulation-based testing is essential for evaluating the safety of Autonomous Driving Systems (ADSs). Comprehensive evaluation requires testing across diverse scenarios that can tr…
Moral Testing of Autonomous Driving Systems
Wenbing Tang, Mingfei Cheng, Yuan Zhou +1
Autonomous Driving System (ADS) testing plays a crucial role in their development, with the current focus primarily on functional and safety testing. However, evaluating the non-fu…