A Review of Current Trends, Techniques, and Challenges in Large Language Models (LLMs)
Grand Valley State University · East Carolina University
Abstract
Natural language processing (NLP) has significantly transformed in the last decade, especially in the field of language modeling. Large language models (LLMs) have achieved SOTA performances on natural language understanding (NLU) and natural language generation (NLG) tasks by learning language representation in self-supervised ways. This paper provides a comprehensive survey to capture the progression of advances in language models. In this paper, we examine the different aspects of language models, which started with a few million parameters but have reached the size of a trillion in a very short time. We also look at how these LLMs transitioned from task-specific to task-independent to…
Citation impact
- FWCI
- 61.74
- Percentile
- 100%
- References
- 73
Authors
2Topics & keywords
- Current (fluid)
- Political science
- Geology
- Quality Education