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What’s the Magic Word? A Control Theory of LLM Prompting.

Machine Learning Street Talk (MLST)

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Exploring Control Mechanisms in Language Models

This chapter explores the intricacies of prompt engineering for language models, highlighting the challenges of trial and error methods in seeking systematic solutions. It discusses a theorem on self-attention mechanisms, the influence of input tokens on outputs, and the benefits of multi-layered architectures over single-layer perceptrons.

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