For a long time, researchers have sought artificial intelligence (AI) that matches or exceeds
human intelligence. AI agents, which are artificial entities capable of sensing the …

Large Language Models (LLMs) went from non-existent to ubiquitous in the machine
learning discourse within a few years. Due to the fast pace of the field, it is difficult to identify …

Large language models are now tuned to align with the goals of their creators, namely to be"
helpful and harmless." These models should respond helpfully to user questions, but refuse …

Large generative AI models (LGAIMs), such as ChatGPT, GPT-4 or Stable Diffusion, are
rapidly transforming the way we communicate, illustrate, and create. However, AI regulation …

Through considerable effort and intuition, several recent works have reverse-engineered
nontrivial behaviors oftransformer models. This paper systematizes the mechanistic …

Artificial Intelligence (AI) has become pervasive, enabling transformative advancements in
various industries including smart city, smart healthcare, smart manufacturing, smart virtual …

Generative image modeling enables a wide range of applications but raises ethical
concerns about responsible deployment. This paper introduces an active strategy combining …

The advancement of artificial intelligence in education (AIED) has the potential to transform
the educational landscape and influence the role of all involved stakeholders. In recent …

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 …