Misinformation such as fake news and rumors is a serious threat for information ecosystems
and public trust. The emergence of large language models (LLMs) has great potential to …

Large language models (LLMs) are a special class of pretrained language models (PLMs)
obtained by scaling model size, pretraining corpus and computation. LLMs, because of their …

As Large Language Models quickly become ubiquitous, their security vulnerabilities are
critical to understand. Recent work shows that text optimizers can produce jailbreaking …

This work identifies 18 foundational challenges in assuring the alignment and safety of large
language models (LLMs). These challenges are organized into three different categories …

Red-teaming is a common practice for mitigating unsafe behaviors in Large Language
Models (LLMs), which involves thoroughly assessing LLMs to identify potential flaws and …

While large language models (LLMs) have shown remarkable effectiveness in various NLP
tasks, they are still prone to issues such as hallucination, unfaithful reasoning, and toxicity. A …

Diffusion models for text-to-image (T2I) synthesis, such as Stable Diffusion (SD), have
recently demonstrated exceptional capabilities for generating high-quality content. However …

In response to rising concerns surrounding the safety, security, and trustworthiness of
Generative AI (GenAI) models, practitioners and regulators alike have pointed to AI red …

The recent success of Large Language Models (LLMs) has catalyzed an increasing interest
in their self-correction capabilities. This paper presents a comprehensive investigation into …

The rapid advancement of Large Language Models (LLMs) has brought about remarkable
capabilities in natural language processing but also raised concerns about their potential …