7 citations · 8 across the 5 of their papers we have counts for
6 papers
EgoExo-WM: Unlocking Exo Video for Ego World Models
Danny Tran, Roberto Martín-Martín, Kristen Grauman
Egocentric world models present a promising direction for enabling agents to predict and plan, but their performance is constrained by the limited availability of egocentric traini…
Understanding the Impact of Geometric Foundation Models on Vision-Language-Action Models
Yurou Yang, Muyuan Lin, Roberto Martin-Martin +4
Recent work explores new opportunities at the intersection of vision-language-action models (VLAs) and geometric foundation models (GFMs) for 3D reconstruction, such as VGGT. While…
Simple Recipe Works: Vision-Language-Action Models are Natural Continual Learners with Reinforcement Learning
Jiaheng Hu, Jay Shim, Chen Tang +4
Continual Reinforcement Learning (CRL) for Vision-Language-Action (VLA) models is a promising direction toward self-improving embodied agents that can adapt in openended, evolving…
Mash, Spread, Slice! Learning to Manipulate Object States via Visual Spatial Progress
Priyanka Mandikal, Jiaheng Hu, Shivin Dass +3
Most robot manipulation focuses on changing the kinematic state of objects: picking, placing, opening, or rotating them. However, a wide range of real-world manipulation tasks invo…
M-EMBER: Tackling Long-Horizon Mobile Manipulation via Factorized Domain Transfer
Bohan Wu, Roberto Martin-Martin, Li Fei-Fei
In this paper, we propose a method to create visuomotor mobile manipulation solutions for long-horizon activities. We propose to leverage the recent advances in simulation to train…
Greedy Hierarchical Variational Autoencoders for Large-Scale Video Prediction
Bohan Wu, Suraj Nair, Roberto Martin-Martin +2
A video prediction model that generalizes to diverse scenes would enable intelligent agents such as robots to perform a variety of tasks via planning with the model. However, while…