Predicting the future trajectories of traffic agents is a pivotal aspect in achieving collision-free
driving for autonomous vehicles. Although the overall accuracy of existing prediction …

Vision-Language Pre-training (VLP) that utilizes the multi-modal information to promote the
training efficiency and effectiveness, has achieved great success in vision recognition of …

In practical applications, the issue of data imbalance inevitably rises. In most studies, the
predominant focus regarding long-tailed class imbalance pertains to a setting within a single …

Text classification is a crucial and fundamental task in natural language processing.
Compared with the previous learning paradigm of pre-training and fine-tuning by cross …

The long-tailed distribution is a common phenomenon in the real world. Extracted large
scale image datasets inevitably demonstrate the long-tailed property and models trained …

In the rapidly expanding field of IoT, data production has reached an unprecedented scale,
providing valuable insights that accelerate decision-making processes. However, ensuring …

There is an inescapable long-tailed class-imbalance issue in many real-world classification
problems. Current methods for addressing this problem only consider scenarios where all …

Real-world data often follows a long-tailed distribution, where a few head classes occupy
most of the data and a large number of tail classes only contain very limited samples. In …

The coronavirus disease 2019 (COVID-19) pneumonia still persists and its chief complaint is
dry cough. Physicians design wireless stethoscopes to facilitate diagnosis, however, lung …

For better performance and less resource consumption, multi-scenario recommendation
(MSR) is proposed to train a unified model to serve all scenarios by leveraging data from …