With the ever‐growing adoption of artificial intelligence (AI)‐based systems, the carbon
footprint of AI is no longer negligible. AI researchers and practitioners are therefore urged to …

Artificial intelligence and machine learning (AI/ML) models have been adopted in a wide
range of healthcare applications, from medical image computing and analysis to continuous …

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 …

This article presents a comprehensive and practical guide for practitioners and end-users
working with Large Language Models (LLMs) in their downstream Natural Language …

Recent years have seen a surge in the popularity of commercial AI products based on
generative, multi-purpose AI systems promising a unified approach to building machine …

Much of the evaluation and tuning of a search system relies on relevance labels---
annotations that say whether a document is useful for a given search and searcher. Ideally …

Recent work in natural language processing (NLP) has yielded appealing results from
scaling model parameters and training data; however, using only scale to improve …

In recent years, the integration of artificial intelligence (AI) and cloud computing has
emerged as a promising avenue for addressing the growing computational demands of AI …

Generative AI technologies such as large language models show novel potential to enhance
educational research. For example, generative large language models were shown to be …

Pretrained language models (PLMs) are trained on massive corpora, but often need to
specialize to specific domains. A parameter-efficient adaptation method suggests training an …