12 citations · 28 across the 16 of their papers we have counts for
17 papers
Encounter-Driven City-Scale Human Mobility Generation with Large Language Models
Chao Li, Renhe Jiang, Chuan Xiao +1
Large language models (LLMs) have shown strong potential for human mobility generation by modeling individual routines, activities, and mobility preferences. However, existing appr…
HEX: Humanoid-Aligned Experts for Cross-Embodiment Whole-Body Manipulation
Shuanghao Bai, Meng Li, Xinyuan Lv +15
Humans achieve complex manipulation through coordinated whole-body control, whereas most Vision-Language-Action (VLA) models treat robot body parts largely independently, making hi…
ManiTwin: Scaling Data-Generation-Ready Digital Object Dataset to 100K
Kaixuan Wang, Tianxing Chen, Jiawei Liu +13
Learning in simulation provides a useful foundation for scaling robotic manipulation capabilities. However, this paradigm often suffers from a lack of data-generation-ready digital…
TrajFlow: Nation-wide Pseudo GPS Trajectory Generation with Flow Matching Models
Peiran Li, Jiawei Wang, Haoran Zhang +4
The importance of mobile phone GPS trajectory data is widely recognized across many fields, yet the use of real data is often hindered by privacy concerns, limited accessibility, a…
ELLMob: Event-Driven Human Mobility Generation with Self-Aligned LLM Framework
Yusong Wang, Chuang Yang, Jiawei Wang +5
Human mobility generation aims to synthesize plausible trajectory data, which is widely used in urban system research. While Large Language Model-based methods excel at generating…
TrajGPT-R: Generating Urban Mobility Trajectory with Reinforcement Learning-Enhanced Generative Pre-trained Transformer
Jiawei Wang, Chuang Yang, Jiawei Yong +6
Mobility trajectories are essential for understanding urban dynamics and enhancing urban planning, yet access to such data is frequently hindered by privacy concerns. This research…
Kinematify: Open-Vocabulary Synthesis of High-DoF Articulated Objects
Jiawei Wang, Dingyou Wang, Jiaming Hu +3
A deep understanding of kinematic structures and movable components is essential for enabling robots to manipulate objects and model their own articulated forms. Such understanding…
TeraSim-World: Worldwide Safety-Critical Data Synthesis for End-to-End Autonomous Driving
Jiawei Wang, Haowei Sun, Xintao Yan +3
Safe and scalable deployment of end-to-end (E2E) autonomous driving requires extensive and diverse data, particularly safety-critical events. Existing data are mostly generated fro…
Improving Traffic Signal Data Quality for the Waymo Open Motion Dataset
Xintao Yan, Erdao Liang, Jiawei Wang +2
Datasets pertaining to autonomous vehicles (AVs) hold significant promise for a range of research fields, including artificial intelligence (AI), autonomous driving, and transporta…
Mobile Manipulation Planning for Tabletop Rearrangement
Jiaming Hu, Jiawei Wang, Henrik I Christensen
Efficient tabletop rearrangement planning seeks to find high-quality solutions while minimizing total cost. However, the task is challenging due to object dependencies and limited…
GSFF-SLAM: 3D Semantic Gaussian Splatting SLAM via Feature Field
Zuxing Lu, Xin Yuan, Shaowen Yang +2
Semantic-aware 3D scene reconstruction is essential for autonomous robots to perform complex interactions. Semantic SLAM, an online approach, integrates pose tracking, geometric re…
cpRRTC: GPU-Parallel RRT-Connect for Constrained Motion Planning
Jiaming Hu, Jiawei Wang, Henrik Christensen
Motion planning is a fundamental problem in robotics that involves generating feasible trajectories for a robot to follow. Recent advances in parallel computing, particularly throu…
RADE: Learning Risk-Adjustable Driving Environment via Multi-Agent Conditional Diffusion
Jiawei Wang, Xintao Yan, Yao Mu +3
Generating safety-critical scenarios in high-fidelity simulations offers a promising and cost-effective approach for efficient testing of autonomous vehicles. Existing methods typi…
TeraSim: Uncovering Unknown Unsafe Events for Autonomous Vehicles through Generative Simulation
Haowei Sun, Xintao Yan, Zhijie Qiao +14
Traffic simulation is essential for autonomous vehicle (AV) development, enabling comprehensive safety evaluation across diverse driving conditions. However, traditional rule-based…
CausalMob: Causal Human Mobility Prediction with LLMs-derived Human Intentions toward Public Events
Xiaojie Yang, Hangli Ge, Jiawei Wang +4
Large-scale human mobility exhibits spatial and temporal patterns that can assist policymakers in decision making. Although traditional prediction models attempt to capture these p…
Large Language Models as Urban Residents: An LLM Agent Framework for Personal Mobility Generation
Jiawei Wang, Renhe Jiang, Chuang Yang +5
This paper introduces a novel approach using Large Language Models (LLMs) integrated into an agent framework for flexible and effective personal mobility generation. LLMs overcome…
XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library
Wenzhang Liu, Wenzhe Cai, Kun Jiang +7
In this paper, we present XuanCe, a comprehensive and unified deep reinforcement learning (DRL) library designed to be compatible with PyTorch, TensorFlow, and MindSpore. XuanCe of…