4.3k citations · 5.9k across the 21 of their papers we have counts for
8 papers · 1 filter
RT-1: Robotics Transformer for Real-World Control at Scale
Anthony Brohan, Noah Brown, Justice Carbajal +48
By transferring knowledge from large, diverse, task-agnostic datasets, modern machine learning models can solve specific downstream tasks either zero-shot or with small task-specif…
Open-vocabulary Queryable Scene Representations for Real World Planning
Boyuan Chen, Fei Xia, Brian Ichter +5
Large language models (LLMs) have unlocked new capabilities of task planning from human instructions. However, prior attempts to apply LLMs to real-world robotic tasks are limited…
Code as Policies: Language Model Programs for Embodied Control
Jacky Liang, Wenlong Huang, Fei Xia +5
Large language models (LLMs) trained on code completion have been shown to be capable of synthesizing simple Python programs from docstrings [1]. We find that these code-writing LL…
Inner Monologue: Embodied Reasoning through Planning with Language Models
Wenlong Huang, Fei Xia, Ted Xiao +14
Recent works have shown how the reasoning capabilities of Large Language Models (LLMs) can be applied to domains beyond natural language processing, such as planning and interactio…
BEHAVIOR in Habitat 2.0: Simulator-Independent Logical Task Description for Benchmarking Embodied AI Agents
Ziang Liu, Roberto Martín-Martín, Fei Xia +2
Robots excel in performing repetitive and precision-sensitive tasks in controlled environments such as warehouses and factories, but have not been yet extended to embodied AI agent…
Do As I Can, Not As I Say: Grounding Language in Robotic Affordances
Michael Ahn, Anthony Brohan, Noah Brown +42
Large language models can encode a wealth of semantic knowledge about the world. Such knowledge could be extremely useful to robots aiming to act upon high-level, temporally extend…
Multi-Robot Active Mapping via Neural Bipartite Graph Matching
Kai Ye, Siyan Dong, Qingnan Fan +5
We study the problem of multi-robot active mapping, which aims for complete scene map construction in minimum time steps. The key to this problem lies in the goal position estimati…
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
Jason Wei, Xuezhi Wang, Dale Schuurmans +6
We explore how generating a chain of thought -- a series of intermediate reasoning steps -- significantly improves the ability of large language models to perform complex reasoning…