Prompting methods such as Chain-of-Thought (CoT) have shed new light on
...
Models trained with empirical risk minimization (ERM) are revealed to ea...
The principle of continual relation extraction (CRE) involves adapting t...
Significant advancements have been made in developing parametric models ...
Large language models have unlocked strong multi-task capabilities from
...
The GPT-3.5 models have demonstrated impressive performance in various
N...
Objective: The objective of this study is to develop a deep-learning bas...
Three-dimensional (3D) ultrasound imaging technique has been applied for...
Adversarial training is one of the most powerful methods to improve the
...
Recent works on Lottery Ticket Hypothesis have shown that pre-trained
la...
Semantic segmentation is a classic computer vision problem dedicated to
...
Ultrasound spine imaging technique has been applied to the assessment of...
Natural language understanding (NLU) models tend to rely on spurious
cor...
Objective: The spinous process angle (SPA) is one of the essential param...
Various robustness evaluation methodologies from different perspectives ...
The growing popularity of mobile and wearable devices with built-in came...