Interpretability In mathematical logic, interpretability is a relation between formal theories that expresses the possibility of interpreting or translating one into the other.

AI interpretability is the ability to understand and explain the decision-making processes that power artificial intelligence models.

First, AI researchers in companies, academia, or nonprofits can accelerate interpretability by directly working on it. Interpretability gets less attention than the constant deluge of model …

Mar 27, 2025 · A description of our new interpretability methods can be found in our first paper, "Circuit tracing: Revealing computational graphs in language models". Many more details of all …

Interpretation is something one does to an explanation with the aim of producing another, more understandable, explanation. As with explanation, there are various concepts and methods …

Oct 10, 2024 · Interpretability describes how easily a human can understand why a machine learning model made a decision. In short, the more interpretable a model is, the more …

Aug 20, 2025 · To better understand their inner workings, two main approaches exist: mechanistic interpretability (precise but impractical) and representation interpretability (practical but …

Interpretability is about mapping an abstract concept from the models into an understandable form. Explainability is a stronger term requiring interpretability and additional context.

2 days ago · Model interpretability research continues to push boundaries, yet scalability and practical deployment remain significant obstacles. Ultimately, the debate over explainability …

The meaning of INTERPRETABILITY is the quality or state of being interpretable. How to use interpretability in a sentence.