The Simple Mathematics of Large Language Models

2026

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AI-generated summary

This paper demystifies large language models by breaking down their core mathematical and statistical underpinnings, making them accessible to a broader audience.

* Explains the fundamental problem of representing text and the statistical objective of language modeling.
* Details the core mechanism of learned weighted averaging and how influence scores are computed.
* Covers essential components like position information, training, and the emergent capabilities and limitations of LLMs.

Tags: Large Language Models, Transformers, Attention Models, Machine Learning, Natural Language Processing

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