Special Issue on Software-Hardware Co-design for Efficient Computing in World Models
Published 26 May, 2026
World Models (WMs) are emerging as the core AI infrastructure for applications like Embodied AI, Autonomous Driving, and VR/AR, enabling capabilities such as imaginative planning and interactive scene generation. However, the rapid increase in model scale leads to exponentially high computational demands, which prevent real-time performance and large-scale deployment. This special issue in Virtual Reality & Intelligent Hardware focuses on Software-Hardware Co-design to achieve efficiency breakthroughs and accelerate the transition of WMs from research to practical application. The special issue will bring together the algorithm, system optimization, and hardware communities to explore the latest advances and challenges in this rapidly evolving domain, with a focus on delivering efficient and scalable computing for WMs. We welcome contributions related to the following (but not limited to) topics:
- Efficient World Model Architecture Design
- Hardware-Friendly World Model Acceleration Methods
- High-Efficiency System Methods for World Models
- Specialized Hardware Architectures for World Models
- Application Systems for Efficient World Models
Submission Deadline:
31 December 2026
Submission Instructions:
Please read the [Guide for Authors] before submitting. All articles should be [submitted online], please select [SI: "Software-Hardware Co-design for EC in WMs"] in VRIH submission system: https://www.editorialmanager.com/vrih/default.aspx
Guest Editors:
Leading Guest Editors
Prof. Xianglong Liu
State Key Laboratory of Software Development Environment, School of Computer Science and Engineering, Beihang University, Beijing, China
Email: xlliu@buaa.edu.cn
Homepage: https://scse.buaa.edu.cn/info/1387/10357.htm
Research Interests: Fast visual computing (e.g., large-scale search/understanding) and robust deep learning (e.g., network quantization, adversarial attack/defense, few shot learning)
Co-Guest Editors
Prof. Jiwen Lu
Department of Automation, Tsinghua University, Beijing, China
Email: lujiwen@tsinghua.edu.cn
Homepage: https://www.au.tsinghua.edu.cn/info/1096/2329.htm
Research Interests: Computer vision, pattern recognition, and machine learning
Prof. Jian Cheng
The Key Laboratory of Cognition and Decision Intelligence for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China
Email: jcheng@nlpr.ia.ac.cn
Homepage: https://people.ucas.ac.cn/~chengjian
Research Interests: Deep learning, computer vision, AI chip design
Prof. Ruihao Gong
State Key Laboratory of Software Development Environment, Beihang University
Email: gongruihao@buaa.edu.cn
Homepage: https://xhplus.github.io/
Research Interests: Efficient deep learning, large models, world models
Prof. Dacheng Tao
College of Computing and Data Science, Nanyang Technological University, Singapore
Email: dacheng.tao@ntu.edu.sg
Homepage: https://dr.ntu.edu.sg/entities/person/Tao-Dacheng/selectedpublications
Research Interests: Computer vision, data mining, deep learning, image processing, and machine learning