16 papers
Point as Skeleton: Accumulated Point Cloud Enhanced Autoregressive Generation for Closed-Loop Autonomous Driving Simulation
Songbur Wong, Xiaosong Jia, Junqi You +12
Evaluating end-to-end autonomous driving (E2E-AD) remains challenging, as existing driving simulation methods often trade off closed-loop interactivity (e.g., CARLA) and real-world…
How Transformers Learn to Plan via Multi-Token Prediction
Jianhao Huang, Zhanpeng Zhou, Renqiu Xia +3
While next-token prediction (NTP) has been the standard objective for training language models, it often struggles to capture global structure in reasoning tasks. Multi-token predi…
DriveVGGT: Calibration-Constrained Visual Geometry Transformers for Multi-Camera Autonomous Driving
Xiaosong Jia, Yanhao Liu, Yu Hong +5
Feed-forward reconstruction has been progressed rapidly, with the Visual Geometry Grounded Transformer (VGGT) being a notable baseline. However, directly applying VGGT to autonomou…
TrustGeoGen: Formal-Verified Data Engine for Trustworthy Multi-modal Geometric Problem Solving
Daocheng Fu, Jianlong Chen, Renqiu Xia +12
Geometric problem solving (GPS) requires precise multimodal understanding and rigorous, step-by-step logical reasoning. However, developing capable Multimodal Large Language Models…
Milestones over Outcome: Unlocking Geometric Reasoning with Sub-Goal Verifiable Reward
Jianlong Chen, Daocheng Fu, Shengze Xu +6
Multimodal Large Language Models (MLLMs) struggle with complex geometric reasoning, largely because "black box" outcome-based supervision fails to distinguish between lucky guesses…
GeoBench: Rethinking Multimodal Geometric Problem-Solving via Hierarchical Evaluation
Yuan Feng, Yue Yang, Xiaohan He +8
Geometric problem solving constitutes a critical branch of mathematical reasoning, requiring precise analysis of shapes and spatial relationships. Current evaluations of geometric…