collaborators

5 papers

eess.SY2026

Hamilton-Jacobi Reachability-Based Safe Reinforcement Learning for Emergency Collision Avoidance

Yuhong Jiang, Shiyue Zhao, Junzhi Zhang +4

Emergency collision avoidance under extreme driving conditions demands safety-critical control that accounts for both obstacle proximity and vehicle dynamic stability over a future…

cs.AI2026

CuraLight: Debate-Guided Data Curation for LLM-Centered Traffic Signal Control

Qing Guo, Xinhang Li, Junyu Chen +4

Traffic signal control (TSC) is a core component of intelligent transportation systems (ITS), aiming to reduce congestion, emissions, and travel time. Recent approaches based on re…

cs.CL2026

Kimi K2.5: Visual Agentic Intelligence

Kimi Team, Tongtong Bai, Yifan Bai +339

We introduce Kimi K2.5, an open-source multimodal agentic model designed to advance general agentic intelligence. K2.5 emphasizes the joint optimization of text and vision so that…

cs.LG2025

A Dual Large Language Models Architecture with Herald Guided Prompts for Parallel Fine Grained Traffic Signal Control

Qing Guo, Xinhang Li, Junyu Chen +4

Leveraging large language models (LLMs) in traffic signal control (TSC) improves optimization efficiency and interpretability compared to traditional reinforcement learning (RL) me…

cs.AI2025

Retrieval Augmented Generation-Enhanced Distributed LLM Agents for Generalizable Traffic Signal Control with Emergency Vehicles

Xinhang Li, Qing Guo, Junyu Chen +4

With increasing urban traffic complexity, Traffic Signal Control (TSC) is essential for optimizing traffic flow and improving road safety. Large Language Models (LLMs) emerge as pr…