8 papers
Platonic Representation Hypothesis on World Models
Wenhow Li, Chengwei MA, Hui Xiong +2
World models have demonstrated significant potential for perceiving and simulating complex environments. Despite their strong performance, the fundamental nature of their learned r…
PatternGSL: A Structured Specification Language for Template-Free and Simulation-Ready 3D Garments
Zhenyang Li, Lutao Jiang, Yizhou Zhao +4
Reconstructing realistic, physically plausible garments from a single image remains a fundamental challenge. Template-free methods capture surface geometry but lack explicit sewing…
Intend, Reflect, Refine: An Adaptive Multimodal Reflection Framework for Autonomous Driving
Zisheng Chen, Yuping Qiu, Jianhua Han +6
Recent Vision-Language-Action (VLA) models have advanced end-to-end autonomous driving by incorporating reasoning for better interpretability and planning quality. However, most ex…
Sat2City v2: Native 3D City Asset Generation from a Single Satellite Image
Tongyan Hua, Dongli Wu, Jinjing Zhu +5
Generating explicit textured 3D city assets from a single satellite image is important for urban simulation and digital twins. Most prior methods, however, learn 3D proxies optimiz…
WorldLines: Benchmarking and Modeling Long-Horizon Stateful Embodied Agents
Yehang Zhang, Jianchong Su, Haojian Huang +7
To assist humans over extended periods in real homes, embodied agents must remember user routines, world states, and past interactions. Existing long-term memory benchmarks mainly…
UniUGP: Unifying Understanding, Generation, and Planing For End-to-end Autonomous Driving
Hao Lu, Ziyang Liu, Guangfeng Jiang +4
Autonomous driving (AD) systems struggle in long-tail scenarios due to limited world knowledge and weak visual dynamic modeling. Existing vision-language-action (VLA)-based methods…
Sage Deer: A Super-Aligned Driving Generalist Is Your Copilot
Hao Lu, Jiaqi Tang, Jiyao Wang +14
The intelligent driving cockpit, an important part of intelligent driving, needs to match different users' comfort, interaction, and safety needs. This paper aims to build a Super-…
The RoboDrive Challenge: Drive Anytime Anywhere in Any Condition
Lingdong Kong, Shaoyuan Xie, Hanjiang Hu +88
In the realm of autonomous driving, robust perception under out-of-distribution conditions is paramount for the safe deployment of vehicles. Challenges such as adverse weather, sen…