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A Primer on Large Language Models and their Limitations

arXiv 2412.04503 ↗First posted 3 Dec 2024cs.CL cs.AIcited by 3

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Abstract (arXiv)

This paper provides a primer on Large Language Models (LLMs) and identifies their strengths, limitations, applications and research directions. It is intended to be useful to those in academia and industry who are interested in gaining an understanding of the key LLM concepts and technologies, and in utilising this knowledge in both day to day tasks and in more complex scenarios where this technology can enhance current practices and processes.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 36 of its 78 references that are in the map. First posted on arXiv 3 Dec 2024.

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36 of 78 references.

References · 36

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24 more
  1. 2021Prefix-Tuning: Optimizing Continuous Prompts for Generationcited by 3,915
  2. 2021Finetuned Language Models Are Zero-Shot Learnerscited by 3,780
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  19. 2024The Ultimate Guide to Fine-Tuning LLMs from Basics to Breakthroughs: An Exhaustive Review of Technologies, Research, Best Practices, Applied Research Challenges and Opportunitiescited by 64
  20. 2020ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generatorscited by 27
  21. 2024YODA: Teacher-Student Progressive Learning for Language Modelscited by 10
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