As dialogue agents become increasingly human-like in their performance, we must develop
effective ways to describe their behaviour in high-level terms without falling into the trap of …

AI alignment aims to make AI systems behave in line with human intentions and values. As
AI systems grow more capable, the potential large-scale risks associated with misaligned AI …

Large language models (LLMs) have been recently leveraged as training data generators
for various natural language processing (NLP) tasks. While previous research has explored …

The utilization of large language models (LLMs) for Healthcare has generated both
excitement and concern due to their ability to effectively respond to free-text queries with …

We explore machine unlearning (MU) in the domain of large language models (LLMs),
referred to as LLM unlearning. This initiative aims to eliminate undesirable data influence …

With the development of large language models (LLMs), striking a balance between the
performance and safety of AI systems has never been more critical. However, the inherent …

In this short consensus paper, we outline risks from upcoming, advanced AI systems. We
examine large-scale social harms and malicious uses, as well as an irreversible loss of …

Nowadays, open-source large language models like LLaMA have emerged. Recent
developments have incorporated supervised fine-tuning (SFT) and reinforcement learning …

Natural language generation has witnessed significant advancements due to the training of
large language models on vast internet-scale datasets. Despite these advancements, there …

Large language models (LLMs) have enabled the generation of high-quality synthetic text,
often indistinguishable from human-written content, at a scale that can markedly affect the …