3 papers
cs.LG2026
Mixture-of-World Models: Scaling Multi-Task Reinforcement Learning with Modular Latent Dynamics
Boxuan Zhang, Weipu Zhang, Zhaohan Feng +4
A fundamental challenge in multi-task reinforcement learning (MTRL) is achieving sample efficiency in visual domains where tasks exhibit substantial heterogeneity in both observati…
cs.RO2025
SPGrasp: Spatiotemporal Prompt-driven Grasp Synthesis in Dynamic Scenes
Yunpeng Mei, Hongjie Cao, Yinqiu Xia +4
Real-time interactive grasp synthesis for dynamic objects remains challenging as existing methods fail to achieve low-latency inference while maintaining promptability. To bridge t…
cs.AI2025
Multi-agent Embodied AI: Advances and Future Directions
Zhaohan Feng, Ruiqi Xue, Lei Yuan +7
Embodied artificial intelligence (Embodied AI) plays a pivotal role in the application of advanced technologies in the intelligent era, where AI systems are integrated with physica…