Aspect-based sentiment classification is a crucial problem in fine-grain...
In this work, we develop and release Llama 2, a collection of pretrained...
Distillation from Weak Teacher (DWT) is a method of transferring knowled...
Many real-world applications require making multiple predictions from th...
Prompt tuning is one of the successful approaches for parameter-efficien...
Whether by processing videos with fixed resolution from start to end or
...
We introduce Progressive Prompts - a simple and efficient approach for
c...
Large multilingual language models typically rely on a single vocabulary...
In this paper, we propose TensorFHE, an FHE acceleration solution based ...
Masked Language Modeling (MLM) has proven to be an essential component o...
As cache-based side-channel attacks become serious security problems, va...
We propose a novel system to help fact-checkers formulate search queries...
The saturating counter is the basic module of the dynamic branch predict...
Prompt tuning is a new, efficient NLP transfer learning paradigm that ad...
Conventional fine-tuning of pre-trained language models tunes all model
...
Cache side channel attacks obtain victim cache line access footprint to ...
Weakly supervised disease classification of CT imaging suffers from poor...
We designed a multi-organ, multi-label disease classification algorithm ...
Recently exposed vulnerabilities reveal the necessity to improve the sec...
Self-supervised learning is showing great promise for monocular depth
es...
Physical activities and social interactions are essential activities tha...
Panoptic segmentation is a complex full scene parsing task requiring
sim...
Recent years have witnessed a significant increase in the online sharing...
Convolutional Neural Network (CNN) based image segmentation has made gre...
There is an urgent demand for privacy-preserving techniques capable of
s...
In this paper, we propose an end-to-end 3D CNN for action detection and
...
Deep learning has been demonstrated to achieve excellent results for ima...