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20242026
most citedTowards Explainable Traffic Flow Prediction with Large Language Models

108 citations · 184 across the 12 of their papers we have counts for

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5 papers · 1 filter

cs.RO2026

Human Behavior-Informed Crash Scenario Generation with Real-World Crash Priors for Autonomous Vehicle Safety Evaluation

Mingxing Peng, Xusen Guo, Long Chen +3

Reliable safety evaluation of autonomous vehicles (AVs) is essential to improving road safety, yet it depends critically on realistic simulation of rare crashes. Existing crash sce…

cs.RO2026

LUNA-AD: Lightweight Uncertainty-Aware Language Model with Lifelong Learning for Autonomous Driving

Ruoyu Yao, Pei Liu, Ruiguo Zhong +3

While large language models (LLMs) offer promising reasoning capabilities, their integration into safety-critical driving systems is hindered by limited reasoning diversity, high c…

cs.RO2026

Decision-Making with Lightweight Confidence-Aware Language Model for Autonomous Driving

Ruoyu Yao, Ruiguo Zhong, Pei Liu +3

Large Language Models (LLMs) and Multimodal LLMs (MLLMs) have demonstrated immense potential in autonomous driving (AD) by offering human-like reasoning and open-world generalizati…

cs.AI2026

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…

cs.AI2026

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…