5 citations · 7 across the 8 of their papers we have counts for
9 papers
InstructMove: A Text-Indispensable Benchmark for Instruction-Following Manipulation
Mengao Zhao, Ziang Li, Chaodong Huang +15
Vision-language-action (VLA) models have made general-purpose robot manipulation increasingly plausible by conditioning robot actions on natural-language instructions. A key test o…
SparseDriveV2: Scoring is All You Need for End-to-End Autonomous Driving
Wenchao Sun, Xuewu Lin, Keyu Chen +4
End-to-end multi-modal planning has been widely adopted to model the uncertainty of driving behavior, typically by scoring candidate trajectories and selecting the optimal one. Exi…
HoloBrain-0 Technical Report
Xuewu Lin, Tianwei Lin, Yun Du +12
In this work, we introduce HoloBrain-0, a comprehensive Vision-Language-Action (VLA) framework that bridges the gap between foundation model research and reliable real-world robot…
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…
SEM: Enhancing Spatial Understanding for Robust Robot Manipulation
Xuewu Lin, Tianwei Lin, Lichao Huang +4
A key challenge in robot manipulation lies in developing policy models with strong spatial understanding, the ability to reason about 3D geometry, object relations, and robot embod…
UniMM: A Unified Mixture Model Framework for Multi-Agent Simulation
Longzhong Lin, Xuewu Lin, Kechun Xu +4
Simulation plays a crucial role in assessing autonomous driving systems, where the generation of realistic multi-agent behaviors is a key aspect. In multi-agent simulation, the pri…
BIP3D: Bridging 2D Images and 3D Perception for Embodied Intelligence
Xuewu Lin, Tianwei Lin, Lichao Huang +2
In embodied intelligence systems, a key component is 3D perception algorithm, which enables agents to understand their surrounding environments. Previous algorithms primarily rely…
EDA: Evolving and Distinct Anchors for Multimodal Motion Prediction
Longzhong Lin, Xuewu Lin, Tianwei Lin +3
Motion prediction is a crucial task in autonomous driving, and one of its major challenges lands in the multimodality of future behaviors. Many successful works have utilized mixtu…
Sparse4D v3: Advancing End-to-End 3D Detection and Tracking
Xuewu Lin, Zixiang Pei, Tianwei Lin +2
In autonomous driving perception systems, 3D detection and tracking are the two fundamental tasks. This paper delves deeper into this field, building upon the Sparse4D framework. W…