4 citations · 7 across the 23 of their papers we have counts for
27 papers
CHOREO: Every Humanoid Skill as a Trajectory
Ziyi Sun, Jingwen Chen, Yuxi Wang +4
Recent advances in humanoid robotics have produced diverse skills through reinforcement learning, motion imitation, and generative modeling. Yet these capabilities remain siloed be…
WorldExam: Benchmarking World Models from Apparent Appearance to Inherent Reactivity
Yuxue Yang, Shuyao Shang, Jiahe Wang +13
Controllable video generation models are increasingly being developed as world models. Accordingly, evaluating them in this role extends beyond the apparent appearance of generated…
PhiZero: A World Model Built Around Physical Language
Shuyao Shang, Yuqi Wang, Ruopeng Gao +4
We introduce PhiZero, a physical world model built around physical language, a compact discrete representation of world-state transitions. Existing physical world models typically…
Embodied-R1.5: Evolving Physical Intelligence via Embodied Foundation Models
Yifu Yuan, Yaoting Huang, Xianze Yao +20
We introduce Embodied-R1.5, a unified Embodied Foundation Model (EFM) that integrates comprehensive embodied reasoning capabilities, spanning embodied cognition, task planning, cor…
World Pilot: Steering Vision-Language-Action Models with World-Action Priors
Zefu Lin, Rongxu Cui, Junjia Xu +4
Vision-Language-Action (VLA) models inherit semantic grounding from large-scale pretraining and perform competently across in-distribution manipulation tasks. This grounding, howev…
DynVLA: Learning World Dynamics for Action Reasoning in Autonomous Driving
Shuyao Shang, Bing Zhan, Yunfei Yan +9
We propose DynVLA, a driving VLA model that introduces a new CoT paradigm termed Dynamics CoT. DynVLA forecasts compact world dynamics before action generation, enabling more infor…
GA-Drive: Geometry-Appearance Decoupled Modeling for Free-viewpoint Driving Scene Generation
Hao Zhang, Lue Fan, Qitai Wang +5
A free-viewpoint, editable, and high-fidelity driving simulator is crucial for training and evaluating end-to-end autonomous driving systems. In this paper, we present GA-Drive, a…
MCOP: Multi-UAV Collaborative Occupancy Prediction
Zefu Lin, Wenbo Chen, Xiaojuan Jin +5
Unmanned Aerial Vehicle (UAV) swarm systems necessitate efficient collaborative perception mechanisms for diverse operational scenarios. Current Bird's Eye View (BEV)-based approac…
EmbodiedCoder: Parameterized Embodied Mobile Manipulation via Modern Coding Model
Zefu Lin, Rongxu Cui, Chen Hanning +8
Recent advances in control robot methods, from end-to-end vision-language-action frameworks to modular systems with predefined primitives, have advanced robots' ability to follow n…
DriveVLA-W0: World Models Amplify Data Scaling Law in Autonomous Driving
Yingyan Li, Shuyao Shang, Weisong Liu +10
Scaling Vision-Language-Action (VLA) models on large-scale data offers a promising path to achieving a more generalized driving intelligence. However, VLA models are limited by a `…
DriveDPO: Policy Learning via Safety DPO For End-to-End Autonomous Driving
Shuyao Shang, Yuntao Chen, Yuqi Wang +2
End-to-end autonomous driving has substantially progressed by directly predicting future trajectories from raw perception inputs, which bypasses traditional modular pipelines. Howe…
UIPro: Unleashing Superior Interaction Capability For GUI Agents
Hongxin Li, Jingran Su, Jingfan Chen +4
Building autonomous agents that perceive and operate graphical user interfaces (GUIs) like humans has long been a vision in the field of artificial intelligence. Central to these a…
Unified Vision-Language-Action Model
Yuqi Wang, Xinghang Li, Wenxuan Wang +5
Vision-language-action models (VLAs) have garnered significant attention for their potential in advancing robotic manipulation. However, previous approaches predominantly rely on t…
TC-Light: Temporally Coherent Generative Rendering for Realistic World Transfer
Yang Liu, Chuanchen Luo, Zimo Tang +6
Illumination and texture editing are critical dimensions for world-to-world transfer, which is valuable for applications including sim2real and real2real visual data scaling up for…
End-to-End Driving with Online Trajectory Evaluation via BEV World Model
Yingyan Li, Yuqi Wang, Yang Liu +3
End-to-end autonomous driving has achieved remarkable progress by integrating perception, prediction, and planning into a fully differentiable framework. Yet, to fully realize its…
FlexDrive: Toward Trajectory Flexibility in Driving Scene Reconstruction and Rendering
Jingqiu Zhou, Lue Fan, Linjiang Huang +4
Driving scene reconstruction and rendering have advanced significantly using the 3D Gaussian Splatting. However, most prior research has focused on the rendering quality along a pr…
LayerAnimate: Layer-level Control for Animation
Yuxue Yang, Lue Fan, Zuzeng Lin +2
Traditional animation production decomposes visual elements into discrete layers to enable independent processing for sketching, refining, coloring, and in-betweening. Existing ani…
DrivingGPT: Unifying Driving World Modeling and Planning with Multi-modal Autoregressive Transformers
Yuntao Chen, Yuqi Wang, Zhaoxiang Zhang
World model-based searching and planning are widely recognized as a promising path toward human-level physical intelligence. However, current driving world models primarily rely on…
FreeSim: Toward Free-viewpoint Camera Simulation in Driving Scenes
Lue Fan, Hao Zhang, Qitai Wang +2
We propose FreeSim, a camera simulation method for autonomous driving. FreeSim emphasizes high-quality rendering from viewpoints beyond the recorded ego trajectories. In such viewp…
FreeVS: Generative View Synthesis on Free Driving Trajectory
Qitai Wang, Lue Fan, Yuqi Wang +2
Existing reconstruction-based novel view synthesis methods for driving scenes focus on synthesizing camera views along the recorded trajectory of the ego vehicle. Their image rende…
DrivingDojo Dataset: Advancing Interactive and Knowledge-Enriched Driving World Model
Yuqi Wang, Ke Cheng, Jiawei He +5
Driving world models have gained increasing attention due to their ability to model complex physical dynamics. However, their superb modeling capability is yet to be fully unleashe…
Monocular Occupancy Prediction for Scalable Indoor Scenes
Hongxiao Yu, Yuqi Wang, Yuntao Chen +1
Camera-based 3D occupancy prediction has recently garnered increasing attention in outdoor driving scenes. However, research in indoor scenes remains relatively unexplored. The cor…
Trim 3D Gaussian Splatting for Accurate Geometry Representation
Lue Fan, Yuxue Yang, Minxing Li +2
In this paper, we introduce Trim 3D Gaussian Splatting (TrimGS) to reconstruct accurate 3D geometry from images. Previous arts for geometry reconstruction from 3D Gaussians mainly…
Enhancing End-to-End Autonomous Driving with Latent World Model
Yingyan Li, Lue Fan, Jiawei He +4
In autonomous driving, end-to-end planners directly utilize raw sensor data, enabling them to extract richer scene features and reduce information loss compared to traditional plan…