AINeutralarXiv – CS AI · 7h ago6/10
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Decomposing how prompting steers behavior
Researchers introduce a geometric decomposition framework to understand how prompting reshapes internal representations in large language models and vision-language models without weight updates. Testing across multiple models and datasets reveals that prompts consistently reorganize representations toward task structures, with cross-dimensional linear mixing (affine transformations) emerging as a key mechanism for prompt-driven behavior.