8 papers
Agents' Last Exam
Yiyou Sun, Xinyang Han, Weichen Zhang +306
Recent AI systems have achieved strong results on a wide range of benchmarks, yet these gains have not translated into economically meaningful deployment across many professional d…
WorldFly: A World-Model-Based Vision-Language-Action Model for UAV Navigation
Shengtao Zheng, Kai Li, Weichen Zhang +5
End-to-end Vision-Language-Action (VLA) models have shown promise in UAV navigation. However, existing approaches typically rely on historical observations to directly predict acti…
SCOPE: Skeleton Graph-Based Computation-Efficient Framework for Autonomous UAV Exploration
Kai Li, Shengtao Zheng, Linkun Xiu +4
Autonomous exploration in unknown environments is key for mobile robots, helping them perceive, map, and make decisions in complex areas. However, current methods often rely on fre…
MARSHAL: Incentivizing Multi-Agent Reasoning via Self-Play with Strategic LLMs
Huining Yuan, Zelai Xu, Zheyue Tan +10
Developing Large Language Models (LLMs) to cooperate and compete effectively within multi-agent systems (MASs) is a critical step towards more advanced intelligence. While reinforc…
QUIDS: Quality-informed Incentive-driven Multi-agent Dispatching System for Mobile Crowdsensing
Nan Zhou, Zuxin Li, Fanhang Man +7
This paper addresses the challenge of achieving optimal Quality of Information (QoI) in non-dedicated vehicular mobile crowdsensing (NVMCS) systems. The key obstacles are the inter…
Flight Dynamics to Sensing Modalities: Exploiting Drone Ground Effect for Accurate Edge Detection
Chenyu Zhao, Jingao Xu, Ciyu Ruan +9
Drone-based rapid and accurate environmental edge detection is highly advantageous for tasks such as disaster relief and autonomous navigation. Current methods, using radars or cam…