Language Model Control
Keith and Tim discuss the controllability of language models, emphasizing the importance of strong prompts to steer model outputs. Shijo from Caltech introduces the self-attention controllability theorem, highlighting the fixed and controllable components in achieving desired model outputs.In this clip
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Machine Learning Street Talk (MLST)
What’s the Magic Word? A Control Theory of LLM Prompting.
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