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

Machine Learning Street Talk (MLST)

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Controlling Language Models Through Prompting

This chapter explores structured prompting methodologies to guide language models, using the example of asserting Roger Federer as the greatest. It delves into the fixed and controllable components of prompting and introduces the self-attention controllability theorem, highlighting the importance of balance for effective language model responses.

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