Challenges and Applications of Large Language Models

TL;DR

This paper reviews the rapid development of Large Language Models, highlighting key challenges and successful applications to help researchers understand the current landscape and identify future directions.

Contribution

It systematically identifies open problems and application successes in LLMs, providing a comprehensive overview of the field's current state.

Findings

Identified key open challenges in LLM development

Documented successful application areas of LLMs

Provided a structured overview for future research directions

Abstract

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 the remaining challenges and already fruitful application areas. In this paper, we aim to establish a systematic set of open problems and application successes so that ML researchers can comprehend the field's current state more quickly and become productive.