Large language models (LLMs) are advanced artificial intelligence (AI) systems that can
perform a variety of tasks commonly found in human intelligence tests, such as defining …

Comprehensively understanding and accurately predicting the performance of large
language models across diverse downstream tasks has emerged as a pivotal challenge in …

Understanding how language model performance varies with scale is critical to benchmark
and algorithm development. Scaling laws are one approach to building this understanding …

Forecasts of future events are essential inputs into informed decision-making. Machine
learning (ML) systems have the potential to deliver forecasts at scale, but there is no …

Guided by the belief of the scaling law, large language models (LLMs) have achieved
impressive performance in recent years. However, scaling law only gives a qualitative …

Can a language model predict for which questions another language model will answer
successfully? We investigate the extent to which performance prediction is possible and …

Scaling laws have driven remarkable progress across machine learning domains like
language modeling and computer vision. However, the exploration of scaling laws in …

Predicting the performance of LLMs on individual task instances is essential to ensure their
reliability in high-stakes applications. To do so, a possibility is to evaluate the considered …

The increasing share of renewable energies within energy systems leads to an increase in
complexity. The growing complexity is due to the diversity of technologies, ongoing …

Abstract Large Language Models (LLMs) gained notable popularity in academia and
industry. It has unprecedented features and performance in many applications. LLMs are …