What is the reaching model?

The concept of the "reaching model" in machine learning typically pertains to the reachability space of models, which is the spectrum of outputs a model can generate based on its input data.

In the context of prompting large language models, the reachability space includes all potential responses or tokens a model could generate. The control theory of prompting suggests that this space is vast and potentially larger than what is constrained by reinforcement learning and human feedback fine-tuning. Despite efforts to streamline responses, the model's ability to produce diverse outputs remains extensive, posing challenges for precision and control in language generation tasks 1.