103 citations · 117 across the 9 of their papers we have counts for
9 papers
VideoWeaver: Evaluating and Evolving Skills for Agentic Long Video Generation
Jianhui Wei, Jie Tan, Hengchuan Zhu +7
Agentic long video generation requires planning, tool orchestration, and cross-clip coordination over a long horizon. Most existing video agents either rely on static, human-crafte…
What Matters in Orchestrating Robot Policies: A Systematic Study of Hierarchical VLA Agents
Jiaheng Hu, Mohit Shridhar, Caden Lu +4
Hierarchical vision-language-action (Hi-VLA) systems have emerged as a promising paradigm for complex robot manipulation, by using high-level VLM planners to decompose tasks into l…
Chain-of-Modality: Learning Manipulation Programs from Multimodal Human Videos with Vision-Language-Models
Chen Wang, Fei Xia, Wenhao Yu +6
Learning to perform manipulation tasks from human videos is a promising approach for teaching robots. However, many manipulation tasks require changing control parameters during ta…
Gemini Robotics: Bringing AI into the Physical World
Gemini Robotics Team, Saminda Abeyruwan, Joshua Ainslie +115
Recent advancements in large multimodal models have led to the emergence of remarkable generalist capabilities in digital domains, yet their translation to physical agents such as…
IPPON: Common Sense Guided Informative Path Planning for Object Goal Navigation
Kaixian Qu, Jie Tan, Tingnan Zhang +3
Navigating efficiently to an object in an unexplored environment is a critical skill for general-purpose intelligent robots. Recent approaches to this object goal navigation proble…
CoNVOI: Context-aware Navigation using Vision Language Models in Outdoor and Indoor Environments
Adarsh Jagan Sathyamoorthy, Kasun Weerakoon, Mohamed Elnoor +6
We present ConVOI, a novel method for autonomous robot navigation in real-world indoor and outdoor environments using Vision Language Models (VLMs). We employ VLMs in two ways: fir…
Learning to Learn Faster from Human Feedback with Language Model Predictive Control
Jacky Liang, Fei Xia, Wenhao Yu +47
Large language models (LLMs) have been shown to exhibit a wide range of capabilities, such as writing robot code from language commands -- enabling non-experts to direct robot beha…
Creative Robot Tool Use with Large Language Models
Mengdi Xu, Peide Huang, Wenhao Yu +7
Tool use is a hallmark of advanced intelligence, exemplified in both animal behavior and robotic capabilities. This paper investigates the feasibility of imbuing robots with the ab…
Open X-Embodiment: Robotic Learning Datasets and RT-X Models
Embodiment Collaboration, Abby O'Neill, Abdul Rehman +291
Large, high-capacity models trained on diverse datasets have shown remarkable successes on efficiently tackling downstream applications. In domains from NLP to Computer Vision, thi…