The rapid development of large language models (LLMs) has opened new avenues across
various fields, including cybersecurity, which faces an evolving threat landscape and …

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 …

Large language models (LLMs) are susceptible to a variety of risks, from non-faithful output
to biased and toxic generations. Due to several limiting factors surrounding LLMs (training …

As generative AI, particularly large language models (LLMs), become increasingly
integrated into production applications, new attack surfaces and vulnerabilities emerge and …

Prior work has explicated the coloniality of artificial intelligence (AI) development and
deployment through mechanisms such as extractivism, automation, sociological …

The alignment of large language models is usually done by model providers to add or
control behaviors that are common or universally understood across use cases and …

Large language models (LLMs) have been rapidly adopted, as showcased by ChatGPT's
overnight popularity, and are integrated in products used by millions of people every day …

The critical inquiry pervading the realm of Philosophy, and perhaps extending its influence
across all Humanities disciplines, revolves around the intricacies of morality and normativity …

As large language models (LLMs) become integrated into everyday applications, ensuring
their robustness and security is increasingly critical. In particular, LLMs can be manipulated …

Generative Foundation Models (GenFMs) have emerged as transformative tools. However,
their widespread adoption raises critical concerns regarding trustworthiness across …