5 papers · 1 filter
Language-Grounded Multi-Agent Planning for Personalized and Fair Participatory Urban Sensing
Xusen Guo, Mingxing Peng, Hongliang Lu +3
Participatory urban sensing leverages human mobility for large-scale urban data collection, yet existing methods typically rely on centralized optimization and assume homogeneous p…
Coordinated Pandemic Control with Large Language Model Agents as Policymaking Assistants
Ziyi Shi, Xusen Guo, Hongliang Lu +7
Effective pandemic control requires timely and coordinated policymaking across administrative regions that are intrinsically interdependent. However, human-driven responses are oft…
AgentSense: LLMs Empower Generalizable and Explainable Web-Based Participatory Urban Sensing
Xusen Guo, Mingxing Peng, Xixuan Hao +4
Web-based participatory urban sensing has emerged as a vital approach for modern urban management by leveraging mobile individuals as distributed sensors. However, existing urban s…
LD-Scene: LLM-Guided Diffusion for Controllable Generation of Adversarial Safety-Critical Driving Scenarios
Mingxing Peng, Yuting Xie, Xusen Guo +3
Ensuring the safety and robustness of autonomous driving systems necessitates a comprehensive evaluation in safety-critical scenarios. However, these safety-critical scenarios are…
Automating Traffic Model Enhancement with AI Research Agent
Xusen Guo, Xinxi Yang, Mingxing Peng +3
Developing efficient traffic models is crucial for optimizing modern transportation systems. However, current modeling approaches remain labor-intensive and prone to human errors d…