Controlling Large Language Model Agents with Entropic Activation
Steering
Controlling Large Language Model Agents with Entropic Activation
Steering
The generality of pretrained large language models (LLMs) has prompted increasing interest in their use as in-context learning agents. To be successful, such agents must form beliefs about how to achieve their goals based on limited interaction with their environment, resulting in uncertainty about the best action to take at …