1 citations · 2 across the 29 of their papers we have counts for
35 papers
Beyond Retrieval Relevance: Scene-Grounded Risk Entailment for Vision-Language Driving
Jiaxin Liu, Ruilin Yu, Liang Peng +8
Retrieval-augmented generation (RAG) gives vision--language driving systems access to external safety knowledge, yet a retrieved risk rule may be relevant without applying to the c…
GeoWorldAD: Geometry World Action Model for Autonomous Driving
Songyan Zhang, Jinyuan Tian, Hanbing Li +9
Autonomous driving requires both safe and efficient planning decisions in dynamic 3D environments. Although recent Vision/Video-Action models learn policies directly from visual ob…
Xiaomi-Robotics-U0: Unified Embodied Synthesis with World Foundation Model
Xinghang Li, Jun Guo, Qiwei Li +21
Recent foundation image and video generation models offer strong generalization and controllability, but their direct application to embodied scenarios is limited by requirements f…
UNIVERSE: Unified Video Action Models for Autonomous Driving with Flexible Mask-Modulated Modality Generation
Mengmeng Liu, Diankun Zhang, Jiuming Liu +7
World Action Models (WAMs) have shown strong potential for improving action generalization in autonomous driving by using future video prediction as dense supervision for scene dyn…
Pondering the Way: Spatial-perceiving World Action Model for Embodied Navigation
Hong Chen, Daqi Liu, Zehan Zhang +10
Existing world model-based planners for visual navigation typically follow a verification-centric paradigm, decoupling goal intent from trajectory synthesis. This approach suffers…
L2D2-GS: Learning to Densify for Feedforward Dynamic Gaussian Scene Reconstruction
Zetian Song, Chenming Wu, Junnan Liu +6
High-fidelity reconstruction of dynamic urban environments is a cornerstone of autonomous driving simulation and large-scale world modeling. While 3D Gaussian Splatting (3DGS) has…
CausalDrive: Real-time Causal World Models for Autonomous Driving
Tianyi Yan, Huan Zheng, Dubing Chen +10
World models have emerged as a promising paradigm for scaling autonomous driving (AD) data, yet existing video generative models fall short as interactive simulators. Layout-condit…
AutoMine Solution for AV2 2026 Scenario Mining Challenge
Songliang Cao, Jiele Zhao, Yuru Wang +10
With the development of autonomous driving systems, mining high-value, safety-critical, and planning-relevant scenarios from large-scale driving logs has become essential for data-…
ReWorld: Representation Learning for World Action Models
Tianze Xia, Lijun Zhou, Kaixin Xiong +8
World Action Models (WAMs) unify future environment prediction with action generation for autonomous driving, yet existing approaches optimize only the final outputs, leaving inter…
PointForward: Feedforward Driving Reconstruction through Point-Aligned Representations
Cheng Chi, Xianqi Wang, Hongcheng Luo +9
High-fidelity reconstruction of driving scenes is crucial for autonomous driving. While recent feedforward 3D Gaussian Splatting (3DGS) methods enable fast reconstruction, their pe…
Xiaomi OneVL: One-Step Latent Reasoning and Planning with Vision-Language Explanation
Jinghui Lu, Jiayi Guan, Zhijian Huang +47
Chain-of-Thought (CoT) reasoning has become a powerful driver of trajectory prediction in VLA-based autonomous driving, yet its autoregressive nature imposes a latency cost that is…
XEmbodied: A Foundation Model with Enhanced Geometric and Physical Cues for Large-Scale Embodied Environments
Kangan Qian, ChuChu Xie, Yang Zhong +13
Vision-Language-Action (VLA) models drive next-generation autonomous systems, but training them requires scalable, high-quality annotations from complex environments. Current cloud…
UniDriveVLA: Unifying Understanding, Perception, and Action Planning for Autonomous Driving
Yongkang Li, Lijun Zhou, Sixu Yan +11
Vision-Language-Action (VLA) models have recently emerged in autonomous driving, with the promise of leveraging rich world knowledge to improve the cognitive capabilities of drivin…
DriveVA: Video Action Models are Zero-Shot Drivers
Mengmeng Liu, Diankun Zhang, Jiuming Liu +7
Generalization is a central challenge in autonomous driving, as real-world deployment requires robust performance under unseen scenarios, sensor domains, and environmental conditio…
Toward Physically Consistent Driving Video World Models under Challenging Trajectories
Jiawei Zhou, Zhenxin Zhu, Lingyi Du +10
Video generation models have shown strong potential as world models for autonomous driving simulation. However, existing approaches are primarily trained on real-world driving data…
LaST-VLA: Thinking in Latent Spatio-Temporal Space for Vision-Language-Action in Autonomous Driving
Yuechen Luo, Fang Li, Shaoqing Xu +10
While Vision-Language-Action (VLA) models have revolutionized autonomous driving by unifying perception and planning, their reliance on explicit textual Chain-of-Thought (CoT) lead…
SEF-MAP: Subspace-Decomposed Expert Fusion for Robust Multimodal HD Map Prediction
Haoxiang Fu, Lingfeng Zhang, Hao Li +7
High-definition (HD) maps are essential for autonomous driving, yet multi-modal fusion often suffers from inconsistency between camera and LiDAR modalities, leading to performance…
UFO: Unifying Feed-Forward and Optimization-based Methods for Large Driving Scene Modeling
Kaiyuan Tan, Yingying Shen, Mingfei Tu +5
Dynamic driving scene reconstruction is critical for autonomous driving simulation and closed-loop learning. While recent feed-forward methods have shown promise for 3D reconstruct…
VGGDrive: Empowering Vision-Language Models with Cross-View Geometric Grounding for Autonomous Driving
Jie Wang, Guang Li, Zhijian Huang +4
The significance of cross-view 3D geometric modeling capabilities for autonomous driving is self-evident, yet existing Vision-Language Models (VLMs) inherently lack this capability…
From Pairs to Sequences: Track-Aware Policy Gradients for Keypoint Detection
Yepeng Liu, Hao Li, Liwen Yang +8
Keypoint-based matching is a fundamental component of modern 3D vision systems, such as Structure-from-Motion (SfM) and SLAM. Most existing learning-based methods are trained on im…
Pixel-Perfect Visual Geometry Estimation
Gangwei Xu, Haotong Lin, Hongcheng Luo +6
Recovering clean and accurate geometry from images is essential for robotics and augmented reality. However, existing geometry foundation models still suffer severely from flying p…
ParkGaussian: Surround-view 3D Gaussian Splatting for Autonomous Parking
Xiaobao Wei, Zhangjie Ye, Yuxiang Gu +10
Parking is a critical task for autonomous driving systems (ADS), with unique challenges in crowded parking slots and GPS-denied environments. However, existing works focus on 2D pa…
Dichotomous Diffusion Policy Optimization
Ruiming Liang, Yinan Zheng, Kexin Zheng +9
Diffusion-based policies have gained growing popularity in solving a wide range of decision-making tasks due to their superior expressiveness and controllable generation during inf…
Mirage: One-Step Video Diffusion for Photorealistic and Coherent Asset Editing in Driving Scenes
Shuyun Wang, Haiyang Sun, Bing Wang +2
Vision-centric autonomous driving systems rely on diverse and scalable training data to achieve robust performance. While video object editing offers a promising path for data augm…