In this work, we develop and release Llama 2, a collection of pretrained and fine-tuned large
language models (LLMs) ranging in scale from 7 billion to 70 billion parameters. Our fine …

Potential harms of large language models can be mitigated by watermarking model output,
ie, embedding signals into generated text that are invisible to humans but algorithmically …

Large generative AI models (LGAIMs), such as ChatGPT, GPT-4 or Stable Diffusion, are
rapidly transforming the way we communicate, illustrate, and create. However, AI regulation …

As increasingly powerful generative AI systems are developed, the release method greatly
varies. We propose a framework to assess six levels of access to generative AI systems: fully …

Calls for representation in artificial intelligence (AI) and machine learning (ML) are
widespread, with" representation" or" representativeness" generally understood to be both …

Building end-to-end task bots and maintaining their integration with new functionalities using
minimal human efforts is a long-standing challenge in dialog research. Recently large …

Generative Artificial Intelligence (GenAI) has emerged as a powerful technology capable of
autonomously producing highly realistic content in various domains, such as text, images …

Artificial Intelligence (AI) is at a crucial point in its development: stable enough to be used in
production systems, and increasingly pervasive in our lives. What does that mean for its …

We find that large language models (LLMs) are more likely to modify human-written text than
AI-generated text when tasked with rewriting. This tendency arises because LLMs often …

In this work, we develop and release Llama 2, a collection of pretrained and fine-tuned large
language models (LLMs) ranging in scale from 7 billion to 70 billion parameters. Our fine …