Large language models (LLMs) have demonstrated remarkable capabilities across a broad
spectrum of tasks. They have attracted significant attention and been deployed in numerous …

Graph neural networks (GNNs) are an emerging research field. This specialized deep
neural network architecture is capable of processing graph structured data and bridges the …

We report the development of GPT-4, a large-scale, multimodal model which can accept
image and text inputs and produce text outputs. While less capable than humans in many …

Aligning large language models (LLMs) with human preferences has proven to drastically
improve usability and has driven rapid adoption as demonstrated by ChatGPT. Alignment …

Large language models are now tuned to align with the goals of their creators, namely to be"
helpful and harmless." These models should respond helpfully to user questions, but refuse …

As the capabilities of generative language models continue to advance, the implications of
biases ingrained within these models have garnered increasing attention from researchers …

Large language models (LLMs), exemplified by ChatGPT, have gained considerable
attention for their excellent natural language processing capabilities. Nonetheless, these …

We describe our early efforts to red team language models in order to simultaneously
discover, measure, and attempt to reduce their potentially harmful outputs. We make three …

Language models (LMs) are pretrained on diverse data sources, including news, discussion
forums, books, and online encyclopedias. A significant portion of this data includes opinions …

Text-to-image models suffer from various safety issues that may limit their suitability for
deployment. Previous methods have separately addressed individual issues of bias …