6 papers
From Digital to Physical: Digital Agents as Autonomous Coaches for Physical Intelligence
Zixing Lei, Genjia Liu, Yuanshuo Zhang +11
The field of Embodied AI is witnessing a rapid evolution toward general-purpose robotic systems, fueled by high-fidelity simulation and large-scale data collection. However, this s…
AstraNav-World: World Model for Foresight Control and Consistency
Jintao Chen, Junjun Hu, Haochen Bai +11
Embodied navigation in open, dynamic environments demands accurate foresight of how the world will evolve and how actions will unfold over time. We propose AstraNav-World, an end-t…
AEGPO: Adaptive Entropy-Guided Policy Optimization for Diffusion Models
Yuming Li, Qingyu Li, Chengyu Bai +6
Reinforcement learning from human feedback (RLHF) shows promise for aligning diffusion and flow models, yet policy optimization methods such as GRPO suffer from inefficient and sta…
UV-M3TL: A Unified and Versatile Multimodal Multi-Task Learning Framework for Assistive Driving Perception
Wenzhuo Liu, Qiannan Guo, Zhen Wang +9
Advanced Driver Assistance Systems (ADAS) need to understand human driver behavior while perceiving their navigation context, but jointly learning these heterogeneous tasks would c…
AFCL: Analytic Federated Continual Learning for Spatio-Temporal Invariance of Non-IID Data
Jianheng Tang, Huiping Zhuang, Jingyu He +10
Federated Continual Learning (FCL) enables distributed clients to collaboratively train a global model from online task streams in dynamic real-world scenarios. However, existing F…
Subgraph Aggregation for Out-of-Distribution Generalization on Graphs
Bowen Liu, Haoyang Li, Shuning Wang +2
Out-of-distribution (OOD) generalization in Graph Neural Networks (GNNs) has gained significant attention due to its critical importance in graph-based predictions in real-world sc…