Large Language Model Steering Vectors are techniques used to guide or control the behavior of large language models by directly manipulating their internal representations. This approach, part of the broader representation engineering framework, involves identifying and modifying activation vectors within the model to achieve desired outputs without requiring additional training or fine-tuning.