21 citations · 26 across the 5 of their papers we have counts for
5 papers
Computer Use at the Edge of the Statistical Precipice
Pierluca D'Oro, Sneha Silwal, William Wong +6
Evaluating Computer Use Agents (CUAs) on interactive environments is fraught with methodological pitfalls that the field has yet to systematically address. We show that a 1MB repla…
DigiData: Training and Evaluating General-Purpose Mobile Control Agents
Yuxuan Sun, Manchen Wang, Shengyi Qian +18
AI agents capable of controlling user interfaces have the potential to transform human interaction with digital devices. To accelerate this transformation, two fundamental building…
What do we learn from a large-scale study of pre-trained visual representations in sim and real environments?
Sneha Silwal, Karmesh Yadav, Tingfan Wu +10
We present a large empirical investigation on the use of pre-trained visual representations (PVRs) for training downstream policies that execute real-world tasks. Our study involve…
Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence?
Arjun Majumdar, Karmesh Yadav, Sergio Arnaud +12
We present the largest and most comprehensive empirical study of pre-trained visual representations (PVRs) or visual 'foundation models' for Embodied AI. First, we curate CortexBen…
Dexterous Imitation Made Easy: A Learning-Based Framework for Efficient Dexterous Manipulation
Sridhar Pandian Arunachalam, Sneha Silwal, Ben Evans +1
Optimizing behaviors for dexterous manipulation has been a longstanding challenge in robotics, with a variety of methods from model-based control to model-free reinforcement learni…