Forgetting refers to the loss or deterioration of previously acquired knowledge. While
existing surveys on forgetting have primarily focused on continual learning, forgetting is a …

Continual learning (CL), or the ability to acquire, process, and learn from new information
without forgetting acquired knowledge, is a fundamental quality of an intelligent agent. The …

The capability of generalizing to out-of-distribution data is crucial for the deployment of
machine learning models in the real world. Existing domain generalization (DG) mainly …

The prevalence of fake news on social media poses devastating and wide-ranging threats to
political beliefs, economic activities, and public health. Due to the continuous emergence of …

Model merging has gained increasing attention as an efficient and effective technique for
integrating task-specific weights from various tasks into a unified multi-task model without …

Deep neural networks suffer from the catastrophic forgetting phenomenon when trained on
sequential tasks in continual learning, especially when data from previous tasks are …

PHEVA, a Privacy-preserving Human-centric Ethical Video Anomaly detection dataset. By
removing pixel information and providing only de-identified human annotations, PHEVA …

Artificial learning systems aspire to mimic human intelligence by continually learning from a
stream of tasks without forgetting past knowledge. One way to enable such learning is to …

Biological brains have the capability to adaptively coordinate relevant neuronal populations
based on the task context to learn continuously changing tasks in real-world environments …

This paper proposes a new continual learning method with Bayesian Compression for
Shared and Private Latent Representations (BCSPLR), which learns a compact model …