489 citations · 1.7k across the 57 of their papers we have counts for
8 papers · 1 filter
ADAPT: Actively Discovering and Adapting to Preferences for any Task
Maithili Patel, Xavier Puig, Ruta Desai +4
Assistive agents should be able to perform under-specified long-horizon tasks while respecting user preferences. We introduce Actively Discovering and Adapting to Preferences for a…
Grounding Multimodal LLMs to Embodied Agents that Ask for Help with Reinforcement Learning
Ram Ramrakhya, Matthew Chang, Xavier Puig +3
Embodied agents operating in household environments must interpret ambiguous and under-specified human instructions. A capable household robot should recognize ambiguity and ask re…
GOAT-Bench: A Benchmark for Multi-Modal Lifelong Navigation
Mukul Khanna, Ram Ramrakhya, Gunjan Chhablani +7
The Embodied AI community has made significant strides in visual navigation tasks, exploring targets from 3D coordinates, objects, language descriptions, and images. However, these…
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…
Factorizing Perception and Policy for Interactive Instruction Following
Kunal Pratap Singh, Suvaansh Bhambri, Byeonghwi Kim +2
Performing simple household tasks based on language directives is very natural to humans, yet it remains an open challenge for AI agents. The 'interactive instruction following' ta…
Rearrangement: A Challenge for Embodied AI
Dhruv Batra, Angel X. Chang, Sonia Chernova +9
We describe a framework for research and evaluation in Embodied AI. Our proposal is based on a canonical task: Rearrangement. A standard task can focus the development of new techn…