The recent release of ChatGPT, a chat bot research project/product of natural language
processing (NLP) by OpenAI, stirs up a sensation among both the general public and …

Pre-trained language models have achieved striking success in natural language
processing (NLP), leading to a paradigm shift from supervised learning to pre-training …

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 …

Language models (LMs) are becoming the foundation for almost all major language
technologies, but their capabilities, limitations, and risks are not well understood. We present …

Spurred by advancements in scale, large language models (LLMs) have demonstrated the
ability to perform a variety of natural language processing (NLP) tasks zero-shot--ie, without …

Abstract We introduce Mind2Web, the first dataset for developing and evaluating generalist
agents for the web that can follow language instructions to complete complex tasks on any …

We propose Unified-IO, a model that performs a large variety of AI tasks spanning classical
computer vision tasks, including pose estimation, object detection, depth estimation and …

Learning on Graphs has attracted immense attention due to its wide real-world applications.
The most popular pipeline for learning on graphs with textual node attributes primarily relies …

Few-shot learning is a challenging task that requires language models to generalize from
limited examples. Large language models like GPT-3 and PaLM have made impressive …

Instruction tuning enables pretrained language models to perform new tasks from inference-
time natural language descriptions. These approaches rely on vast amounts of human …