3 citations · 3 across the 4 of their papers we have counts for
5 papers
Posterior Augmented Flow Matching
George Stoica, Sayak Paul, Matthew Wallingford +6
Flow matching (FM) trains a time-dependent vector field that transports samples from a simple prior to a complex data distribution. However, for high-dimensional images, each train…
Resolving Interference (RI): Disentangling Models for Improved Model Merging
Pratik Ramesh, George Stoica, Arun Iyer +2
Model merging has shown that multitask models can be created by directly combining the parameters of different models that are each specialized on tasks of interest. However, model…
Emergence of Human to Robot Transfer in Vision-Language-Action Models
Simar Kareer, Karl Pertsch, James Darpinian +5
Vision-language-action (VLA) models can enable broad open world generalization, but require large and diverse datasets. It is appealing to consider whether some of this data can co…
EgoBridge: Domain Adaptation for Generalizable Imitation from Egocentric Human Data
Ryan Punamiya, Dhruv Patel, Patcharapong Aphiwetsa +5
Egocentric human experience data presents a vast resource for scaling up end-to-end imitation learning for robotic manipulation. However, significant domain gaps in visual appearan…
EgoMimic: Scaling Imitation Learning via Egocentric Video
Simar Kareer, Dhruv Patel, Ryan Punamiya +5
The scale and diversity of demonstration data required for imitation learning is a significant challenge. We present EgoMimic, a full-stack framework which scales manipulation via…