206 citations · 488 across the 15 of their papers we have counts for
5 papers · 1 filter
Patching open-vocabulary models by interpolating weights
Gabriel Ilharco, Mitchell Wortsman, Samir Yitzhak Gadre +5
Open-vocabulary models like CLIP achieve high accuracy across many image classification tasks. However, there are still settings where their zero-shot performance is far from optim…
Structure from Action: Learning Interactions for Articulated Object 3D Structure Discovery
Neil Nie, Samir Yitzhak Gadre, Kiana Ehsani +1
We introduce Structure from Action (SfA), a framework to discover 3D part geometry and joint parameters of unseen articulated objects via a sequence of inferred interactions. Our k…
Continuous Scene Representations for Embodied AI
Samir Yitzhak Gadre, Kiana Ehsani, Shuran Song +1
We propose Continuous Scene Representations (CSR), a scene representation constructed by an embodied agent navigating within a space, where objects and their relationships are mode…
CoWs on Pasture: Baselines and Benchmarks for Language-Driven Zero-Shot Object Navigation
Samir Yitzhak Gadre, Mitchell Wortsman, Gabriel Ilharco +2
For robots to be generally useful, they must be able to find arbitrary objects described by people (i.e., be language-driven) even without expensive navigation training on in-domai…
Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time
Mitchell Wortsman, Gabriel Ilharco, Samir Yitzhak Gadre +8
The conventional recipe for maximizing model accuracy is to (1) train multiple models with various hyperparameters and (2) pick the individual model which performs best on a held-o…