The last two years have seen a rapid growth in concerns around the safety of large
language models (LLMs). Researchers and practitioners have met these concerns by …

Software Engineering (SE) is the systematic design, development, maintenance, and
management of software applications underpinning the digital infrastructure of our modern …

Large language models (LLM) have demonstrated emergent abilities in text generation,
question answering, and reasoning, facilitating various tasks and domains. Despite their …

Rigorous and reproducible evaluation is critical for assessing the state of the art and for
guiding scientific advances in Artificial Intelligence. Evaluation is challenging in practice due …

The rapid progress in Large Language Models (LLMs) poses potential risks such as
generating unethical content. Assessing LLMs' values can help expose their misalignment …

AI Safety is an emerging area of critical importance to the safe adoption and deployment of
AI systems. With the rapid proliferation of AI and especially with the recent advancement of …

Large Language Models (LLMs) have recently gained attention due to their ability to
understand and generate sophisticated human-like content. However, ensuring their safety …

As Large Language Models (LLMs) achieve remarkable breakthroughs, aligning their
values with humans has become imperative for their responsible development and …

Large Language Models (LLMs) have become an integral part of our daily lives. However,
they impose certain risks, including those that can harm individuals' privacy, perpetuate …

Evaluations are limited by benchmark availability. As models evolve, there is a need to
create benchmarks that can measure progress on new generative capabilities. However …