Zobrazeno 1 - 10
of 588
pro vyhledávání: '"KONG Tao"'
Autor:
Kong Tao, Xu Shan, Binbo He, Qingyu Zeng, Meirong Wu, Liu Jie, Wenfeng Yuan, Hu Dan, Zhang Tao
Publikováno v:
Therapeutic Advances in Gastroenterology, Vol 17 (2024)
Background: Esophageal-gastric variceal bleeding (EGVB) is a serious complication in patients with liver cirrhosis, characterized by high mortality and rebleeding rates. The effect of sequential endoscopic therapy on patient mortality and rebleeding
Externí odkaz:
https://doaj.org/article/762342075ccc4f98b02873be609a3ba4
Autor:
Cheang, Chi-Lam, Chen, Guangzeng, Jing, Ya, Kong, Tao, Li, Hang, Li, Yifeng, Liu, Yuxiao, Wu, Hongtao, Xu, Jiafeng, Yang, Yichu, Zhang, Hanbo, Zhu, Minzhao
We present GR-2, a state-of-the-art generalist robot agent for versatile and generalizable robot manipulation. GR-2 is first pre-trained on a vast number of Internet videos to capture the dynamics of the world. This large-scale pre-training, involvin
Externí odkaz:
http://arxiv.org/abs/2410.06158
Autor:
Lai, Hang, Cao, Jiahang, Xu, Jiafeng, Wu, Hongtao, Lin, Yunfeng, Kong, Tao, Yu, Yong, Zhang, Weinan
Legged locomotion over various terrains is challenging and requires precise perception of the robot and its surroundings from both proprioception and vision. However, learning directly from high-dimensional visual input is often data-inefficient and
Externí odkaz:
http://arxiv.org/abs/2409.16784
The robotics community has consistently aimed to achieve generalizable robot manipulation with flexible natural language instructions. One of the primary challenges is that obtaining robot data fully annotated with both actions and texts is time-cons
Externí odkaz:
http://arxiv.org/abs/2408.14368
Scalable robot learning in the real world is limited by the cost and safety issues of real robots. In addition, rolling out robot trajectories in the real world can be time-consuming and labor-intensive. In this paper, we propose to learn an interact
Externí odkaz:
http://arxiv.org/abs/2406.14540
Linguistic ambiguity is ubiquitous in our daily lives. Previous works adopted interaction between robots and humans for language disambiguation. Nevertheless, when interactive robots are deployed in daily environments, there are significant challenge
Externí odkaz:
http://arxiv.org/abs/2402.11792
Interactive visual grounding in Human-Robot Interaction (HRI) is challenging yet practical due to the inevitable ambiguity in natural languages. It requires robots to disambiguate the user input by active information gathering. Previous approaches of
Externí odkaz:
http://arxiv.org/abs/2401.16699
Autor:
Wu, Hongtao, Jing, Ya, Cheang, Chilam, Chen, Guangzeng, Xu, Jiafeng, Li, Xinghang, Liu, Minghuan, Li, Hang, Kong, Tao
Generative pre-trained models have demonstrated remarkable effectiveness in language and vision domains by learning useful representations. In this paper, we extend the scope of this effectiveness by showing that visual robot manipulation can signifi
Externí odkaz:
http://arxiv.org/abs/2312.13139
Autor:
Li, Xinghang, Liu, Minghuan, Zhang, Hanbo, Yu, Cunjun, Xu, Jie, Wu, Hongtao, Cheang, Chilam, Jing, Ya, Zhang, Weinan, Liu, Huaping, Li, Hang, Kong, Tao
Recent progress in vision language foundation models has shown their ability to understand multimodal data and resolve complicated vision language tasks, including robotics manipulation. We seek a straightforward way of making use of existing vision-
Externí odkaz:
http://arxiv.org/abs/2311.01378
Ambiguity is ubiquitous in human communication. Previous approaches in Human-Robot Interaction (HRI) have often relied on predefined interaction templates, leading to reduced performance in realistic and open-ended scenarios. To address these issues,
Externí odkaz:
http://arxiv.org/abs/2310.12147