90 citations · 121 across the 10 of their papers we have counts for
11 papers
Training-Free Action Correction for VLA Model Failures via Language Feedback
Owen Kwon, Pablo Ortega-Kral, Arthur Bucker +1
Vision-Language-Action (VLA) models demonstrate strong semantic understanding yet exhibit systematic failures during deployment. The conditions under which these failures occur, an…
RIO: Flexible Real-Time Robot I/O for Cross-Embodiment Robot Learning
Pablo Ortega-Kral, Eliot Xing, Arthur Bucker +13
Despite recent efforts to collect multi-task, multi-embodiment datasets, to design recipes for training Vision-Language-Action models (VLAs), and to showcase these models on differ…
GRAPPA: Generalizing and Adapting Robot Policies via Online Agentic Guidance
Arthur Bucker, Pablo Ortega-Kral, Jonathan Francis +1
Robot learning approaches such as behavior cloning and reinforcement learning have shown great promise in synthesizing robot skills from human demonstrations in specific environmen…
Windows Agent Arena: Evaluating Multi-Modal OS Agents at Scale
Rogerio Bonatti, Dan Zhao, Francesco Bonacci +9
Large language models (LLMs) show remarkable potential to act as computer agents, enhancing human productivity and software accessibility in multi-modal tasks that require planning…
ChatGPT for Robotics: Design Principles and Model Abilities
Sai Vemprala, Rogerio Bonatti, Arthur Bucker +1
This paper presents an experimental study regarding the use of OpenAI's ChatGPT for robotics applications. We outline a strategy that combines design principles for prompt engineer…
LATTE: LAnguage Trajectory TransformEr
Arthur Bucker, Luis Figueredo, Sami Haddadin +4
Natural language is one of the most intuitive ways to express human intent. However, translating instructions and commands towards robotic motion generation and deployment in the r…