Large language models in machine learning

Key Points

• The aim is to analyze the evolution and challenges of large language models in machine learning.
• Review of literature on large language models and their architectural innovations.
• Analysis of training techniques specific to LLMs.
• Evaluation of applications and metrics used for assessing LLM performance.
• LLMs demonstrate unprecedented capabilities in natural language processing tasks.
• Insights into both the advancements and limitations of current LLMs are provided.
• The review suggests future research directions for further development in the field.

Abstract