collaborators

8 papers

cs.HC2026

Who Responds When the Driver Is Gone? A Framework for Holistic Passenger Intent Understanding

Xuewen Luo, Ding Fan, Ruiqi Chen +5

As autonomous vehicles advance toward driverless mobility, understanding and responding to passenger needs and intentions becomes increasingly important in the absence of a human d…

cs.AI2026

CIVIC: End-to-End Sequence Compactness for Efficient Vision-Language Models

Fengze Yang, Bo Yu, Xuewen Luo +2

Vision-Language Models (VLMs) face severe memory and latency bottlenecks due to high-resolution visual tokens. While current token reduction methods theoretically save FLOPs, post-…

cs.RO2026

KnowDiffuser: A Knowledge-Guided Diffusion Planner with LLM Reasoning

Fan Ding, Xuewen Luo, Fengze Yang +4

Recent advancements in Language Models (LMs) have demonstrated strong semantic reasoning capabilities, enabling their application in high-level decision-making for autonomous drivi…

cs.CV2026

Locatability-Guided Adaptive Reasoning for Image Geo-Localization with Vision-Language Models

Bo Yu, Fengze Yang, Yiming Liu +6

The emergence of Vision-Language Models (VLMs) has introduced new paradigms for global image geo-localization through retrieval-augmented generation (RAG) and reasoning-driven infe…

cs.AI2025

Edge-Based Multimodal Sensor Data Fusion with Vision Language Models (VLMs) for Real-time Autonomous Vehicle Accident Avoidance

Fengze Yang, Bo Yu, Yang Zhou +3

Autonomous driving (AD) systems relying solely on onboard sensors may fail to detect distant or obstacle hazards, potentially causing preventable collisions; however, existing tran…

cs.AI2025

V2X-UniPool: Unifying Multimodal Perception and Knowledge Reasoning for Autonomous Driving

Xuewen Luo, Fengze Yang, Fan Ding +5

Autonomous driving (AD) has achieved significant progress, yet single-vehicle perception remains constrained by sensing range and occlusions. Vehicle-to-Everything (V2X) communicat…

cs.AI2025

Independent Mobility GPT (IDM-GPT): A Self-Supervised Multi-Agent Large Language Model Framework for Customized Traffic Mobility Analysis Using Machine Learning Models

Fengze Yang, Xiaoyue Cathy Liu, Lingjiu Lu +2

With the urbanization process, an increasing number of sensors are being deployed in transportation systems, leading to an explosion of big data. To harness the power of this vast…

cs.AI2025

SenseRAG: Constructing Environmental Knowledge Bases with Proactive Querying for LLM-Based Autonomous Driving

Xuewen Luo, Fan Ding, Fengze Yang +4

This study addresses the critical need for enhanced situational awareness in autonomous driving (AD) by leveraging the contextual reasoning capabilities of large language models (L…