14 citations · 60 across the 27 of their papers we have counts for
32 papers
KineWorld: Action-Induced Transport Fields for Embodied World Modeling
Ziying Song, Yuchen Liu, Zhuoran Xu +6
Embodied world models predict the visual consequences of candidate actions before execution. However, existing action-conditioned world models often adopt uniformly weighted visual…
Controllable and Photorealistic Pedestrian Risky Motion Generation for End-to-End Driving Safety Evaluation
Siyuan Liu, Miao Li, Haibao Yu +4
Evaluating end-to-end autonomous driving under rare, safety-critical vehicle-pedestrian interactions requires photorealistic, sensor-level scenarios. However, trajectory-based scen…
PRICE the Action Chunks: Physical Relational Credit Assignment for Embodied Reinforcement Learning
Yangang Zou, Jiajun Lu, Weitao Zhou +6
Outcome-based reinforcement learning (RL) post-trains vision--language--action policies using terminal success signals, but assigns the same trajectory-level advantage to every act…
InfraOcc: An Infrastructure Occupancy Benchmark with Static-to-Dynamic Reasoning
Lei Yang, Xiaokai Bai, Boqi Li +8
Fixed-viewpoint infrastructure sensors repeatedly observe the same traffic space, making roadside 3D occupancy structurally different from ego-vehicle perception: a near-persistent…
KnockGS:interaction-Grounded Calibrationof Physical Gaussian Representations
Chenchen Ge, Hanwen Shen, Bowen Jing +6
Physics-integrated 3D Gaussian representations now allow reconstructed deformable objects to be simulated and rendered under explicit material models. Existing pipelines, however,…
GaussianDream++: Efficient 3D Gaussian World Modeling for Robotic Manipulation
Yuqing Jiang, Zijian Zhang, Weitao Zhou +8
Vision-Language-Action (VLA) policies have advanced language-conditioned robotic manipulation, yet action-imitation objectives provide only weak supervision for metric 3D structure…
GaussianWAM: Distilling Geometry and Semantics from 3D Gaussian Fields into World-Action Models
Zijian Zhang, Yuqing Jiang, Weitao Zhou +6
World-Action Models (WAMs) jointly learn future visual prediction and action generation, using video dynamics as a representation-learning signal for robotic manipulation. However,…
SoftVTBench: A Deformation-Aware Visuo-Tactile Dataset and Benchmark for Deformable-Object Manipulation
Bowen Jing, Mingxin Wang, Ruiyang Hao +15
Physical interaction quality is central to deformable-object manipulation, yet most benchmarks evaluate task success alone. A policy may complete the task while allowing slip or ca…
SoftVTBench: A Safety-Aware Visuo-Tactile Benchmark for Physically Constrained Robotic Manipulation of Deformable Objects (Early Version)
Bowen Jing, Mingxin Wang, Ruiyang Hao +15
Deformable object manipulation poses challenges beyond task completion: successful execution must also maintain safe physical interaction, holding the object stably without slip or…
RoboDojo: A Unified Sim-and-Real Benchmark for Comprehensive Evaluation of Generalist Robot Manipulation Policies
Tianxing Chen, Yue Chen, Zixuan Li +41
Generalist robot manipulation policies have advanced rapidly, yet existing benchmarks remain limited in systematically evaluating their capabilities. Many rely on simple, short-hor…
AR Forcing: Towards Long-Horizon Robot Navigation World Model
Yifei Yang, Zehua Fan, Huan Li +9
The diffusion based robot navigation world models are typically trained using parallel supervision, while autoregressive inference is employed during path planning. This results in…
GaussianDream: A Feed-Forward 3D Gaussian World Model for Robotic Manipulation
Zijian Zhang, Yuqing Jiang, Qian Cheng +6
Vision-language-action (VLA) policies have advanced language-conditioned robotic manipulation by transferring semantic priors from pretrained vision-language models to action gener…
CounterScene: Counterfactual Causal Reasoning in Generative World Models for Safety-Critical Closed-Loop Evaluation
Bowen Jing, Ruiyang Hao, Weitao Zhou +1
Generating safety-critical driving scenarios requires understanding why dangerous interactions arise, rather than merely forcing collisions. However, existing methods rely on heuri…
SparseCoop: Cooperative Perception with Kinematic-Grounded Queries
Jiahao Wang, Zhongwei Jiang, Wenchao Sun +8
Cooperative perception is critical for autonomous driving, overcoming the inherent limitations of a single vehicle, such as occlusions and constrained fields-of-view. However, curr…
UniMM-V2X: MoE-Enhanced Multi-Level Fusion for End-to-End Cooperative Autonomous Driving
Ziyi Song, Chen Xia, Chenbing Wang +3
Autonomous driving holds transformative potential but remains fundamentally constrained by the limited perception and isolated decision-making with standalone intelligence. While r…
DriveE2E: Closed-Loop Benchmark for End-to-End Autonomous Driving through Real-to-Simulation
Haibao Yu, Wenxian Yang, Ruiyang Hao +4
Closed-loop evaluation is increasingly critical for end-to-end autonomous driving. Current closed-loop benchmarks using the CARLA simulator rely on manually configured traffic scen…
Research Challenges and Progress in the End-to-End V2X Cooperative Autonomous Driving Competition
Ruiyang Hao, Haibao Yu, Jiaru Zhong +16
With the rapid advancement of autonomous driving technology, vehicle-to-everything (V2X) communication has emerged as a key enabler for extending perception range and enhancing dri…
CoopTrack: Exploring End-to-End Learning for Efficient Cooperative Sequential Perception
Jiaru Zhong, Jiahao Wang, Jiahui Xu +3
Cooperative perception aims to address the inherent limitations of single-vehicle autonomous driving systems through information exchange among multiple agents. Previous research h…
Benchmarking Generalizable Bimanual Manipulation: RoboTwin Dual-Arm Collaboration Challenge at CVPR 2025 MEIS Workshop
Tianxing Chen, Kaixuan Wang, Zhaohui Yang +96
Embodied Artificial Intelligence (Embodied AI) is an emerging frontier in robotics, driven by the need for autonomous systems that can perceive, reason, and act in complex physical…
StyleDrive: Towards Driving-Style Aware Benchmarking of End-To-End Autonomous Driving
Ruiyang Hao, Bowen Jing, Haibao Yu +1
Personalization, while extensively studied in conventional autonomous driving pipelines, has been largely overlooked in the context of end-to-end autonomous driving (E2EAD), despit…
Griffin: Aerial-Ground Cooperative Detection and Tracking Dataset and Benchmark
Jiahao Wang, Xiangyu Cao, Jiaru Zhong +7
While cooperative perception can overcome the limitations of single-vehicle systems, the practical implementation of vehicle-to-vehicle and vehicle-to-infrastructure systems is oft…
LiDAR-based End-to-end Temporal Perception for Vehicle-Infrastructure Cooperation
Zhenwei Yang, Jilei Mao, Wenxian Yang +4
Temporal perception, defined as the capability to detect and track objects across temporal sequences, serves as a fundamental component in autonomous driving systems. While single-…
Leveraging Temporal Contexts to Enhance Vehicle-Infrastructure Cooperative Perception
Jiaru Zhong, Haibao Yu, Tianyi Zhu +4
Infrastructure sensors installed at elevated positions offer a broader perception range and encounter fewer occlusions. Integrating both infrastructure and ego-vehicle data through…
End-to-End Autonomous Driving through V2X Cooperation
Haibao Yu, Wenxian Yang, Jiaru Zhong +4
Cooperatively utilizing both ego-vehicle and infrastructure sensor data via V2X communication has emerged as a promising approach for advanced autonomous driving. However, current…