Large Language Models (LLMs) went from non-existent to ubiquitous in the machine
learning discourse within a few years. Due to the fast pace of the field, it is difficult to identify …

Machine learning (ML) provides novel and powerful ways of accurately and efficiently
recognizing complex patterns, emulating nonlinear dynamics, and predicting the spatio …

Recent work claims that large language models display\textit {emergent abilities}, abilities
not present in smaller-scale models that are present in larger-scale models. What makes …

Novel functional materials enable fundamental breakthroughs across technological
applications from clean energy to information processing,,,,,,,,,–. From microchips to batteries …

Scaling up neural networks has led to remarkable performance across a wide range of
tasks. Moreover, performance often follows reliable scaling laws as a function of training set …

Large language models (LLMs) have been shown to be able to perform new tasks based on
a few demonstrations or natural language instructions. While these capabilities have led to …

Large-scale diffusion-based generative models have led to breakthroughs in text-
conditioned high-resolution image synthesis. Starting from random noise, such text-to-image …

We introduce phi-1, a new large language model for code, with significantly smaller size
than competing models: phi-1 is a Transformer-based model with 1.3 B parameters, trained …

Widely observed neural scaling laws, in which error falls off as a power of the training set
size, model size, or both, have driven substantial performance improvements in deep …

How well can NLP models generalize to a variety of unseen tasks when provided with task
instructions? To address this question, we first introduce Super-NaturalInstructions, a …