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 …

Prepending model inputs with safety prompts is a common practice for safeguarding large
language models (LLMs) against queries with harmful intents. However, the underlying …

Powered by advanced Artificial Intelligence (AI) techniques, conversational AI systems, such
as ChatGPT, and digital assistants like Siri, have been widely deployed in daily life …

Most existing dialogue systems fail to respond properly to potentially unsafe user utterances
by either ignoring or passively agreeing with them. To address this issue, we introduce …

Automated dialogue or conversational systems are anthropomorphised by developers and
personified by users. While a degree of anthropomorphism may be inevitable due to the …

Chatbots are used in many applications, eg, automated agents, smart home assistants,
interactive characters in online games, etc. Therefore, it is crucial to ensure they do not …

Offensive language detection is increasingly crucial for maintaining a civilized social media
platform and deploying pre-trained language models. However, this task in Chinese is still …

This open access book provides a comprehensive overview of the state of the art in research
and applications of Foundation Models and is intended for readers familiar with basic …

The social impact of natural language processing and its applications has received
increasing attention. In this position paper, we focus on the problem of safety for end-to-end …

From pre-trained language model (PLM) to large language model (LLM), the field of natural
language processing (NLP) has witnessed steep performance gains and wide practical …