The integration of Generative Artificial Intelligence (AI) into autonomous machines
represents a major paradigm shift in how these systems operate and unlocks new solutions …

Continual Learning aims to empower a single model to continually adapt to novel
environments and perform new tasks while retaining previous knowledge without …

Recent research on large language models (LLMs) has demonstrated their ability to
understand and employ deceptive behavior, even without explicit prompting. However, such …

The advancements in generative AI inevitably raise concerns about their risks and safety
implications, which, in return, catalyzes significant progress in AI safety. However, as this …

As the application of large language models continues to expand in various fields, it poses
higher challenges to the effectiveness of identifying harmful content generation and …

In this manuscript, we provide a comprehensive overview of the various work done while
using Gen-AI techniques wrt user safety. In particular, we first provide the various domains …

As generative AI systems, including large language models (LLMs) and diffusion models,
advance rapidly, their growing adoption has led to new and complex security risks often …

The rapid advancement of Large Language Models (LLMs) has introduced significant
challenges in moderating user-model interactions. While LLMs demonstrate remarkable …

Abstract Retrieval-Augmented Generation (RAG) has significantly enhanced the capabilities
of Large Language Models (LLMs) by enabling them to access and incorporate external …