4 citations · 5 across the 14 of their papers we have counts for
14 papers
Turning Stale Gradients into Stable Gradients: Coherent Coordinate Descent with Implicit Landscape Smoothing for Lightweight Zeroth-Order Optimization
Chen Liang, Xiatao Sun, Qian Wang +1
Zeroth-Order (ZO) optimization is pivotal for scenarios where backpropagation is unavailable, such as memory-constrained on-device learning and black-box optimization. However, exi…
RuleSmith: Multi-Agent LLMs for Automated Game Balancing
Ziyao Zeng, Chen Liu, Tianyu Liu +11
Game balancing is a longstanding challenge requiring repeated playtesting, expert intuition, and extensive manual tuning. We introduce RuleSmith, a framework that couples multi-age…
Subsecond 3D Mesh Generation for Robot Manipulation
Qian Wang, Omar Abdellall, Tony Gao +2
3D meshes are a fundamental representation widely used in computer science and engineering. In robotics, they are particularly valuable because they capture objects in a form that…
Mesh RAG: Retrieval Augmentation for Autoregressive Mesh Generation
Xiatao Sun, Chen Liang, Qian Wang +1
3D meshes are a critical building block for applications ranging from industrial design and gaming to simulation and robotics. Traditionally, meshes are crafted manually by artists…
Hybrid Diffusion Policies with Projective Geometric Algebra for Efficient Robot Manipulation Learning
Xiatao Sun, Yuxuan Wang, Shuo Yang +2
Diffusion policies are a powerful paradigm for robot learning, but their training is often inefficient. A key reason is that networks must relearn fundamental spatial concepts, suc…
PRISM-DP: Spatial Pose-based Observations for Diffusion-Policies via Segmentation, Mesh Generation, and Pose Tracking
Xiatao Sun, Yinxing Chen, Daniel Rakita
Diffusion policies generate robot motions by learning to denoise action-space trajectories conditioned on observations. These observations are commonly streams of RGB images, whose…
Dynamic Rank Adjustment in Diffusion Policies for Efficient and Flexible Training
Xiatao Sun, Shuo Yang, Yinxing Chen +3
Diffusion policies trained via offline behavioral cloning have recently gained traction in robotic motion generation. While effective, these policies typically require a large numb…
Developing Path Planning with Behavioral Cloning and Proximal Policy Optimization for Path-Tracking and Static Obstacle Nudging
Mingyan Zhou, Biao Wang, Tian Tan +1
In autonomous driving, end-to-end methods utilizing Imitation Learning (IL) and Reinforcement Learning (RL) are becoming more and more common. However, they do not involve explicit…
Optimizing Active Perception for Learning Simultaneous Viewpoint Selection and Manipulation with Diffusion Policy
Xiatao Sun, Francis Fan, Yinxing Chen +1
Robotic manipulation tasks often rely on static cameras for perception, which can limit flexibility, particularly in scenarios like robotic surgery and cluttered environments where…
Deep Learning for Optimization of Trajectories for Quadrotors
Yuwei Wu, Xiatao Sun, Igor Spasojevic +1
This paper presents a novel learning-based trajectory planning framework for quadrotors that combines model-based optimization techniques with deep learning. Specifically, we formu…
MEGA-DAgger: Imitation Learning with Multiple Imperfect Experts
Xiatao Sun, Shuo Yang, Mingyan Zhou +2
Imitation learning has been widely applied to various autonomous systems thanks to recent development in interactive algorithms that address covariate shift and compounding errors…
Multi-Agent Exploration of an Unknown Sparse Landmark Complex via Deep Reinforcement Learning
Xiatao Sun, Yuwei Wu, Subhrajit Bhattacharya +1
In recent years Landmark Complexes have been successfully employed for localization-free and metric-free autonomous exploration using a group of sensing-limited and communication-l…
A Benchmark Comparison of Imitation Learning-based Control Policies for Autonomous Racing
Xiatao Sun, Mingyan Zhou, Zhijun Zhuang +3
Autonomous racing with scaled race cars has gained increasing attention as an effective approach for developing perception, planning and control algorithms for safe autonomous driv…
Drive Right: Shaping Public's Trust, Understanding, and Preference Towards Autonomous Vehicles Using a Virtual Reality Driving Simulator
Zhijie Qiao, Xiatao Sun, Helen Loeb +1
Autonomous vehicles are increasingly introduced into our lives. Yet, people's misunderstanding and mistrust have become the major obstacles to the use of these technologies. In res…