activity
20242026
most citedAutoTrust: Benchmarking Trustworthiness in Large Vision Language Models for Autonomous Driving

2 citations · 3 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2026

Visko Orbis 1.0: A Live Model for Real-Time Interactive Long Video Generation

Xiangbo Gao, Siyuan Yang, Ping He +12

We present Visko Orbis 1.0, a Live Model for real-time, interactive long video generation. Users can change the prompt at any moment during generation, and the update becomes visib…

cs.CV2025

Demystifying the Visual Quality Paradox in Multimodal Large Language Models

Shuo Xing, Lanqing Guo, Hongyuan Hua +5

Recent Multimodal Large Language Models (MLLMs) excel on benchmark vision-language tasks, yet little is known about how input visual quality shapes their responses. Does higher per…

cs.CV2025

Generative AI for Autonomous Driving: Frontiers and Opportunities

Yuping Wang, Shuo Xing, Cui Can +44

Generative Artificial Intelligence (GenAI) constitutes a transformative technological wave that reconfigures industries through its unparalleled capabilities for content creation,…

cs.CV2024★ 1 cited

OpenEMMA: Open-Source Multimodal Model for End-to-End Autonomous Driving

Shuo Xing, Chengyuan Qian, Yuping Wang +4

Since the advent of Multimodal Large Language Models (MLLMs), they have made a significant impact across a wide range of real-world applications, particularly in Autonomous Driving…

cs.CV2024★ 2 cited

AutoTrust: Benchmarking Trustworthiness in Large Vision Language Models for Autonomous Driving

Shuo Xing, Hongyuan Hua, Xiangbo Gao +10

Recent advancements in large vision language models (VLMs) tailored for autonomous driving (AD) have shown strong scene understanding and reasoning capabilities, making them undeni…