As artificial intelligence (AI) continues to rapidly evolve, the realm of Earth and atmospheric
sciences is increasingly adopting data-driven models, powered by progressive …

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

Over the recent years, large pretrained language models (LM) have revolutionized the field
of natural language processing (NLP). However, while pretraining on general language has …

Since they started to recognise the potential to cut costs, boost productivity, and achieve
greater levels of quality, many firms have been adjusting their operations to a process …

With the exponential growth of computational power and the availability of large-scale
datasets in recent years, remarkable advancements have been made in the field of artificial …

This paper introduces ClimateGPT, a model family of domain-specific large language
models that synthesize interdisciplinary research on climate change. We trained two 7B …

This paper presents an impartial and extensive benchmark for text classification involving
five different text classification tasks, 20 datasets, 11 different model architectures, and …

Large language models (LLMs) have significantly transformed the landscape of artificial
intelligence by demonstrating their ability in generating human-like text across diverse …

How do we roll out language technologies across a world with 7,000 languages? In one
story, we scale the successes of NLP further into'low-resource'languages, doing ever more …

Corporate climate disclosures are considered an essential prerequisite to managing climate-
related financial risks. At the same time, current disclosures are imprecise, inaccurate, and …