3 citations · 4 across the 8 of their papers we have counts for
9 papers
Training-Free Multi-Agent Cooperative Embodied Search from Uncertain Vision-Language Priors
Fan Pu, Keshu Wu, Jiwan Jiang +5
Real-world Vision-Language Navigation (VLN) requires agents to act under partial observability, where map structure, semantic cues, and target locations may be incomplete or incorr…
Stochastic and Dynamic Fundamental Diagram for Mixed Traffic
Jiwan Jiang, Soyoung Ahn
This study develops a dynamic fundamental diagram (FD) framework tailored to mixed traffic environments comprising automated vehicles (AVs) and human-driven vehicles (HDVs). Descri…
Knowledge Is Not Static: Order-Aware Hypergraph RAG for Language Models
Keshu Wu, Chenchen Kuai, Zihao Li +6
Retrieval-augmented generation (RAG) enhances large language models by grounding outputs in retrieved knowledge. However, existing RAG methods including graph- and hypergraph-based…
A Statistical Framework for Auditing Behavioral Dependence and Induced Bias in LLM Judges
Chenchen Kuai, Jiwan Jiang, Zihao Zhu +8
The rapid growth of the large language model (LLM) ecosystem raises a critical question: are seemingly diverse models truly independent? Shared pretraining data, distillation, and…
Unveiling Traffic Wave of Linear Adaptive Cruise Control: A Second-order Macroscopic Traffic Flow Model
Zihao Li, Quyuan Lin, Fan Pu +4
Traffic waves, the spatiotemporal propagation of congestion, are a key feature of traffic flow. As Adaptive Cruise Control (ACC) systems gain widespread adoption and show promise f…
Simulating the Unseen: Crash Prediction Must Learn from What Did Not Happen
Zihao Li, Xinyuan Cao, Xiangbo Gao +12
Traffic safety science has long been hindered by a fundamental data paradox: the crashes we most wish to prevent are precisely those events we rarely observe. Existing crash-freque…
NuScenes-SpatialQA: A Spatial Understanding and Reasoning Benchmark for Vision-Language Models in Autonomous Driving
Kexin Tian, Jingrui Mao, Yunlong Zhang +3
Recent advancements in Vision-Language Models (VLMs) have demonstrated strong potential for autonomous driving tasks. However, their spatial understanding and reasoning-key capabil…
A Generic Stochastic Hybrid Car-following Model Based on Approximate Bayesian Computation
Jiwan Jiang, Yang Zhou, Xin Wang +1
Car following (CF) models are fundamental to describing traffic dynamics. However, the CF behavior of human drivers is highly stochastic and nonlinear. As a result, identifying the…
Sequencing-enabled Hierarchical Cooperative CAV On-ramp Merging Control with Enhanced Stability and Feasibility
Sixu Li, Yang Zhou, Xinyue Ye +2
This paper develops a sequencing-enabled hierarchical connected automated vehicle (CAV) cooperative on-ramp merging control framework. The proposed framework consists of a two-laye…