Network-based Intrusion Detection System (NIDS) forms the frontline defence against
network attacks that compromise the security of the data, systems, and networks. In recent …

Self-supervised learning (SSL) has recently achieved impressive performance on various
time series tasks. The most prominent advantage of SSL is that it reduces the dependence …

Cross-entropy is a widely used loss function in applications. It coincides with the logistic loss
applied to the outputs of a neural network, when the softmax is used. But, what guarantees …

Recent text-to-image diffusion models such as MidJourney and Stable Diffusion threaten to
displace many in the professional artist community. In particular, models can learn to mimic …

Automated red teaming holds substantial promise for uncovering and mitigating the risks
associated with the malicious use of large language models (LLMs), yet the field lacks a …

This work identifies 18 foundational challenges in assuring the alignment and safety of large
language models (LLMs). These challenges are organized into three different categories …

The extraordinary ability of generative models to generate photographic images has
intensified concerns about the spread of disinformation, thereby leading to the demand for …

Graph representation learning aims to effectively encode high-dimensional sparse graph-
structured data into low-dimensional dense vectors, which is a fundamental task that has …

Autonomous vehicles (AVs), defined as vehicles capable of navigation and decision-making
independent of human intervention, represent a revolutionary advancement in transportation …

Large Vision-Language Models (LVLMs) signify a groundbreaking paradigm shift within the
Artificial Intelligence (AI) community, extending beyond the capabilities of Large Language …