60 citations · 155 across the 19 of their papers we have counts for
4 papers · 1 filter
Mastering Robot Manipulation with Multimodal Prompts through Pretraining and Multi-task Fine-tuning
Jiachen Li, Qiaozi Gao, Michael Johnston +6
Prompt-based learning has been demonstrated as a compelling paradigm contributing to large language models' tremendous success (LLMs). Inspired by their success in language tasks,…
LEMMA: Learning Language-Conditioned Multi-Robot Manipulation
Ran Gong, Xiaofeng Gao, Qiaozi Gao +3
Complex manipulation tasks often require robots with complementary capabilities to collaborate. We introduce a benchmark for LanguagE-Conditioned Multi-robot MAnipulation (LEMMA) f…
Language-Informed Transfer Learning for Embodied Household Activities
Yuqian Jiang, Qiaozi Gao, Govind Thattai +1
For service robots to become general-purpose in everyday household environments, they need not only a large library of primitive skills, but also the ability to quickly learn novel…
Learning to Act with Affordance-Aware Multimodal Neural SLAM
Zhiwei Jia, Kaixiang Lin, Yizhou Zhao +3
Recent years have witnessed an emerging paradigm shift toward embodied artificial intelligence, in which an agent must learn to solve challenging tasks by interacting with its envi…