81 citations · 90 across the 6 of their papers we have counts for
6 papers
InSTA: Towards Internet-Scale Training For Agents
Brandon Trabucco, Gunnar Sigurdsson, Robinson Piramuthu +1
The predominant approach for training web navigation agents is to gather human demonstrations for a set of popular websites and hand-written tasks, but it is becoming clear that hu…
Understanding Visual Concepts Across Models
Brandon Trabucco, Max Gurinas, Kyle Doherty +1
Large multimodal models such as Stable Diffusion can generate, detect, and classify new visual concepts after fine-tuning just a single word embedding. Do models learn similar word…
Leafy Spurge Dataset: Real-world Weed Classification Within Aerial Drone Imagery
Kyle Doherty, Max Gurinas, Erik Samsoe +5
Invasive plant species are detrimental to the ecology of both agricultural and wildland areas. Euphorbia esula, or leafy spurge, is one such plant that has spread through much of N…
Stylus: Automatic Adapter Selection for Diffusion Models
Michael Luo, Justin Wong, Brandon Trabucco +5
Beyond scaling base models with more data or parameters, fine-tuned adapters provide an alternative way to generate high fidelity, custom images at reduced costs. As such, adapters…
Effective Data Augmentation With Diffusion Models
Brandon Trabucco, Kyle Doherty, Max Gurinas +1
Data augmentation is one of the most prevalent tools in deep learning, underpinning many recent advances, including those from classification, generative models, and representation…
A Simple Approach for Visual Rearrangement: 3D Mapping and Semantic Search
Brandon Trabucco, Gunnar Sigurdsson, Robinson Piramuthu +2
Physically rearranging objects is an important capability for embodied agents. Visual room rearrangement evaluates an agent's ability to rearrange objects in a room to a desired go…