This paper presents a novel approach to enhance autonomous robotic
manip...
Currently, most machine learning models are trained by centralized teams...
Sparsely activated neural networks with conditional computation learn to...
The volume of scientific output is creating an urgent need for automated...
Producing high-quality forecasts of key climate variables such as temper...
Few-shot in-context learning (ICL) enables pre-trained language models t...
Despite the success of fine-tuning pretrained language encoders like BER...
Recent years have seen numerous NLP datasets introduced to evaluate the
...
One reason pretraining on self-supervised linguistic tasks is effective ...
A growing body of work shows that models exploit annotation artifacts to...
Performance on the Winograd Schema Challenge (WSC), a respected English
...
Intermediate-task training has been shown to substantially improve pretr...
While pretrained models such as BERT have shown large gains across natur...
We introduce jiant, an open source toolkit for conducting multitask and
...
We introduce The Benchmark of Linguistic Minimal Pairs (shortened to BLi...
Though state-of-the-art sentence representation models can perform tasks...