312 citations · 615 across the 9 of their papers we have counts for
13 papers
ProcTHOR: Large-Scale Embodied AI Using Procedural Generation
Matt Deitke, Eli VanderBilt, Alvaro Herrasti +8
Massive datasets and high-capacity models have driven many recent advancements in computer vision and natural language understanding. This work presents a platform to enable simila…
Webly Supervised Concept Expansion for General Purpose Vision Models
Amita Kamath, Christopher Clark, Tanmay Gupta +3
General Purpose Vision (GPV) systems are models that are designed to solve a wide array of visual tasks without requiring architectural changes. Today, GPVs primarily learn both sk…
Asymptotic behavior of the free interface for entire vector minimizers in phase transitions
Nicholas D. Alikakos, Zhiyuan Geng, Arghir Zarnescu
We study globally bounded entire minimizers of Allen-Cahn systems for potentials with and $W(u)\sim |u-a…
CORA: Benchmarks, Baselines, and Metrics as a Platform for Continual Reinforcement Learning Agents
Sam Powers, Eliot Xing, Eric Kolve +2
Progress in continual reinforcement learning has been limited due to several barriers to entry: missing code, high compute requirements, and a lack of suitable benchmarks. In this…
ManipulaTHOR: A Framework for Visual Object Manipulation
Kiana Ehsani, Winson Han, Alvaro Herrasti +5
The domain of Embodied AI has recently witnessed substantial progress, particularly in navigating agents within their environments. These early successes have laid the building blo…
A Cordial Sync: Going Beyond Marginal Policies for Multi-Agent Embodied Tasks
Unnat Jain, Luca Weihs, Eric Kolve +4
Autonomous agents must learn to collaborate. It is not scalable to develop a new centralized agent every time a task's difficulty outpaces a single agent's abilities. While multi-a…