With the ongoing rapid adoption of Artificial Intelligence (AI)-based systems in high-stakes
domains, ensuring the trustworthiness, safety, and observability of these systems has …

Jailbreak attacks cause large language models (LLMs) to generate harmful, unethical, or
otherwise objectionable content. Evaluating these attacks presents a number of challenges …

The rapid rise in popularity of Large Language Models (LLMs) with emerging capabilities
has spurred public curiosity to evaluate and compare different LLMs, leading many …

This study embarks on an exploration of the performance disparities observed between
English and Chinese in large language models (LLMs), motivated by the growing need for …

This study went on a comprehensive evaluation of four prominent Large Language Models
(LLMs)-Google Gemini, Mistral 8x7B, ChatGPT-4, and Microsoft Phi-1.5-to assess their …

The safety evaluation of large language models against adversarial prompt injections
introduces a novel and significant concept that addresses the critical need for robust AI …

Large foundation models (LFMs) are claiming incredible performances. Yet great concerns
have been raised about their mythic and uninterpreted potentials not only in machine …

Since the emergence of large language models, prompt learning has become a popular
method for optimizing and customizing these models. Special prompts, such as Chain-of …

Modern language models (LMs) pose a new challenge in capability assessment. Static
benchmarks inevitably saturate without providing confidence in the deployment tolerances …

Model editing aims to correct outdated or erroneous knowledge in large language models
(LLMs) without the need for costly retraining. Lifelong model editing is the most challenging …