7 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…
BrainMem: Brain-Inspired Evolving Memory for Embodied Agent Task Planning
Xiaoyu Ma, Lianyu Hu, Wenbing Tang +4
Embodied task planning requires agents to execute long-horizon, goal-directed actions in complex 3D environments, where success depends on both immediate perception and accumulated…
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…
Shedding Light on VLN Robustness: A Black-box Framework for Indoor Lighting-based Adversarial Attack
Chenyang Li, Wenbing Tang, Yihao Huang +4
Vision-and-Language Navigation (VLN) agents have made remarkable progress, but their robustness remains insufficiently studied. Existing adversarial evaluations often rely on pertu…
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…