2 citations · 2 across the 8 of their papers we have counts for
11 papers
RoXDrive: Closed-Loop Reinforcement Learning for End-to-End Autonomous Driving via Action-Faithful Rollouts
Hongbin Lin, Chaoda Zheng, Yiming Yang +11
End-to-end autonomous driving policies are commonly trained via imitation learning on logged demonstrations without observing the consequences of their own actions, leading to caus…
Modeling Clinical Workflow for SYNTAX Scoring from Coronary Angiography Videos
Suzhong Fu, Jingqi Dong, Xuan Ding +4
The SYNTAX score is a clinically established tool for assessing anatomical lesion complexity in coronary artery disease and guiding subsequent treatment. However, automated SYNTAX…
Reasoning to Regulate: Chain-of-Thought for Traffic Rule Understanding
Yueru Luo, Xu Yan, Changqing Zhou +5
Understanding and complying with traffic regulations is a safety-critical requirement for autonomous driving, yet remains challenging due to the diversity and context dependence of…
AgentsEval: Clinically Faithful Evaluation of Medical Imaging Reports via Multi-Agent Reasoning
Suzhong Fu, Jingqi Dong, Xuan Ding +4
Evaluating the clinical correctness and reasoning fidelity of automatically generated medical imaging reports remains a critical yet unresolved challenge. Existing evaluation metho…
VesSAM: Efficient Multi-Prompting for Segmenting Complex Vessel
Suzhong Fu, Rui Sun, Xuan Ding +8
Accurate vessel segmentation is critical for clinical applications such as disease diagnosis and surgical planning, yet remains challenging due to thin, branching structures and lo…
FutureX: Enhance End-to-End Autonomous Driving via Latent Chain-of-Thought World Model
Hongbin Lin, Yiming Yang, Yifan Zhang +10
In autonomous driving, end-to-end planners learn scene representations from raw sensor data and utilize them to generate a motion plan or control actions. However, exclusive relian…
DriveFlow: Rectified Flow Adaptation for Robust 3D Object Detection in Autonomous Driving
Hongbin Lin, Yiming Yang, Chaoda Zheng +7
In autonomous driving, vision-centric 3D object detection recognizes and localizes 3D objects from RGB images. However, due to high annotation costs and diverse outdoor scenes, tra…
FASTopoWM: Fast-Slow Lane Segment Topology Reasoning with Latent World Models
Yiming Yang, Hongbin Lin, Yueru Luo +7
Lane segment topology reasoning provides comprehensive bird's-eye view (BEV) road scene understanding, which can serve as a key perception module in planning-oriented end-to-end au…
TopoStreamer: Temporal Lane Segment Topology Reasoning in Autonomous Driving
Yiming Yang, Yueru Luo, Bingkun He +8
Lane segment topology reasoning constructs a comprehensive road network by capturing the topological relationships between lane segments and their semantic types. This enables end-…
Geometry-Guided Representations for Coherent Lane and Traffic Topology Reasoning in Driving Scenes
Yueru Luo, Changqing Zhou, Yiming Yang +4
Road topology reasoning is fundamental for autonomous driving, requiring both accurate perception of road elements and understanding of their complex connectivity, including lane c…
Topo2Seq: Enhanced Topology Reasoning via Topology Sequence Learning
Yiming Yang, Yueru Luo, Bingkun He +5
Extracting lane topology from perspective views (PV) is crucial for planning and control in autonomous driving. This approach extracts potential drivable trajectories for self-driv…