8 papers
MARS: Systematic Multi-Level Acceleration for World Action Models
Zengyuan Zuo, Yongchang Zhang, Guangyu Zhao +4
World Action Models (WAMs) have emerged as a promising alternative for embodied intelligence by jointly predicting future world states and robot actions. However, their heavy visua…
EgoSteer: An Open-Source Full-Stack System Towards Steerable Dexterous Manipulation from Egocentric Videos
Yifan Zhong, Zhang Chen, Tianrui Guan +15
The enduring vision of general-purpose robots serving humanity hinges fundamentally on policy steerability. However, prevailing paradigms of learning from expert demonstrations dem…
Preserve Support, Not Correspondence: Dynamic Routing for Offline Reinforcement Learning
Zhancun Mu, Guangyu Zhao, Yiwu Zhong +1
One-step offline RL actors are attractive because they avoid backpropagating through long iterative samplers and keep inference cheap, but they still have to improve under a critic…
System Design for Maintaining Internal State Consistency in Long-Horizon Robotic Tabletop Games
Guangyu Zhao, Ceyao Zhang, Chengdong Ma +16
Long-horizon tabletop games pose a distinct systems challenge for robotics: small perceptual or execution errors can invalidate accumulated task state, propagate across decision-ma…
When Robots Should Say "I Don't Know": Benchmarking Abstention in Embodied Question Answering
Tao Wu, Chuhao Zhou, Guangyu Zhao +3
Embodied Question Answering (EQA) requires an agent to interpret language, perceive its environment, and navigate within 3D scenes to produce responses. Existing EQA benchmarks ass…
Preference Goal Tuning: Post-Training as Latent Control for Frozen Policies
Guangyu Zhao, Kewei Lian, Haoxuan Ru +8
Goal-conditioned policies enable decision-making models to execute diverse behaviors based on specified goals, yet their downstream performance is often highly sensitive to the cho…
Whole-Body Control Through Narrow Gaps From Pixels To Action
Tianyue Wu, Yeke Chen, Tianyang Chen +2
Flying through body-size narrow gaps in the environment is one of the most challenging moments for an underactuated multirotor. We explore a purely data-driven method to master thi…
Learning Speed Adaptation for Flight in Clutter
Guangyu Zhao, Tianyue Wu, Yeke Chen +1
Animals learn to adapt speed of their movements to their capabilities and the environment they observe. Mobile robots should also demonstrate this ability to trade-off aggressivene…