5 papers
Enhancing Generalization in Vision-Language-Action Models by Preserving Pretrained Representations
Shresth Grover, Akshay Gopalkrishnan, Bo Ai +3
Vision-language-action (VLA) models finetuned from vision-language models (VLMs) hold the promise of leveraging rich pretrained representations to build generalist robots across di…
Do Vision-Language Models Have Internal World Models? Towards an Atomic Evaluation
Qiyue Gao, Xinyu Pi, Kevin Liu +21
Internal world models (WMs) enable agents to understand the world's state and predict transitions, serving as the basis for advanced deliberative reasoning. Recent large Vision-Lan…
Towards Embodiment Scaling Laws in Robot Locomotion
Bo Ai, Liu Dai, Nico Bohlinger +7
Cross-embodiment generalization underpins the vision of building generalist embodied agents for any robot, yet its enabling factors remain poorly understood. We investigate embodim…
Learning Adaptive Dexterous Grasping from Single Demonstrations
Liangzhi Shi, Yulin Liu, Lingqi Zeng +3
How can robots learn dexterous grasping skills efficiently and apply them adaptively based on user instructions? This work tackles two key challenges: efficient skill acquisition f…
Diffusion Dynamics Models with Generative State Estimation for Cloth Manipulation
Tongxuan Tian, Haoyang Li, Bo Ai +3
Cloth manipulation is challenging due to its highly complex dynamics, near-infinite degrees of freedom, and frequent self-occlusions, which complicate both state estimation and dyn…