Summary of A Primer on Large Language Models and Their Limitations, by Sandra Johnson and David Hyland-wood
A Primer on Large Language Models and their Limitations
by Sandra Johnson, David Hyland-Wood
First submitted to arxiv on: 3 Dec 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper provides a comprehensive overview of Large Language Models (LLMs), highlighting their strengths, limitations, and applications. The primer aims to equip academia and industry professionals with a solid understanding of LLM concepts and technologies, enabling them to leverage this knowledge in various scenarios. Specifically, the authors identify key research directions and potential uses of LLMs in everyday tasks and more complex processes. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Large Language Models are powerful tools that can help us understand and work with human language better. This paper explains what LLMs are, how they work, and why they’re important. It’s like a guidebook for anyone who wants to learn about this technology and use it to make their work or life easier. |
