Existing robotic systems have a clear tension between generality and
pre...
Various design settings for in-context learning (ICL), such as the choic...
The fixed-size context of Transformer makes GPT models incapable of
gene...
Large language models appear to learn facts from the large text corpora ...
RGB-thermal salient object detection (RGB-T SOD) aims to locate the comm...
Representation learning on graphs, also called graph embedding, has
demo...
Graph neural networks (GNNs) have been widely used for representation
le...
Pretrained language models (LMs) do not capture factual knowledge very w...
Within the field of robotic manipulation, a central goal is to replicate...
NLP has a rich history of representing our prior understanding of langua...
This paper derives a closed-form method for computing hybrid force-veloc...
The discontinuities and multi-modality introduced by contacts make
manip...
Graph neural networks (GNNs) have attracted much attention because of th...
A shared grasp is a grasp formed by contacts between the manipulated obj...
We consider the problem of reorienting a rigid object with arbitrary kno...
In hybrid force-velocity control, the robot can use velocity control in ...
We present an algorithm for obtaining an optimal control policy for hybr...