4 citations · 4 across the 8 of their papers we have counts for
10 papers
WA-JEPA: Rethinking the Video JEPA Paradigm for World-Action Modeling in Autonomous Driving
Xinlin Wang, Yujiao Xiang, Yuheng Zhou +11
Video Joint Embedding Predictive Architecture (V-JEPA) learns powerful spatiotemporal representations from video through self-supervised latent feature prediction. However, V-JEPA…
Walking in the Implicit: Interactive World Exploration via Neural Scene Representation
Zhiqi Li, Chengrui Dong, Zhenhua Du +6
Interactive video generation systems for camera-controlled world exploration roll out growing sequences of latent video frames, entangling state transition with high-frequency obse…
ChainFlow-VLA: Causal Flow Planning with Vision-Language Models
Xiyang Wang, Xinlin Wang, Tingguang Zhou +7
Current end-to-end autonomous driving systems are fundamentally limited by a mismatch between temporal causal reasoning and global trajectory consistency. Autoregressive (AR) model…
SDGBiasBench: Benchmarking and Mitigating Vision--Language Models' Biases in Sustainable Development Goals
Zihang Lin, Huaiyuan Qin, Muli Yang +1
Assessing progress toward the Sustainable Development Goals (SDGs) requires multi-step reasoning over visual cues, contextual knowledge, and development indicators, where incomplet…
CoWorld-VLA: Thinking in a Multi-Expert World Model for Autonomous Driving
Minqing Huang, Yujiao Xiang, Zihan Liang +8
Vision-Language-Action (VLA) models have emerged as a promising paradigm for end-to-end autonomous driving. However, existing reasoning mechanisms still struggle to provide plannin…
Any 3D Scene is Worth 1K Tokens: 3D-Grounded Representation for Scene Generation at Scale
Dongxu Wei, Qi Xu, Zhiqi Li +6
Scene-level 3D generation has long been dominated by 2D multi-view or video diffusion models. Typically, these 2D-based approaches perform scene generation in a 2D latent space, wh…
Autoregressive Meta-Actions for Unified Controllable Trajectory Generation
Jianbo Zhao, Taiyu Ban, Xiyang Wang +6
Controllable trajectory generation guided by high-level semantic decisions, termed meta-actions, is crucial for autonomous driving systems. A significant limitation of existing fra…
DRoPE: Directional Rotary Position Embedding for Efficient Agent Interaction Modeling
Jianbo Zhao, Taiyu Ban, Zhihao Liu +7
Accurate and efficient modeling of agent interactions is essential for trajectory generation, the core of autonomous driving systems. Existing methods, scene-centric, agent-centric…
UniScene: Unified Occupancy-centric Driving Scene Generation
Bohan Li, Jiazhe Guo, Hongsi Liu +14
Generating high-fidelity, controllable, and annotated training data is critical for autonomous driving. Existing methods typically generate a single data form directly from a coars…
MCTrack: A Unified 3D Multi-Object Tracking Framework for Autonomous Driving
Xiyang Wang, Shouzheng Qi, Jieyou Zhao +8
This paper introduces MCTrack, a new 3D multi-object tracking method that achieves state-of-the-art (SOTA) performance across KITTI, nuScenes, and Waymo datasets. Addressing the ga…