Reflection (artificial intelligence)

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It has been suggested that Reasoning language model be merged into this article. (Discuss) Proposed since April 2025.

Reflection in artificial intelligence, notably used in large language models, specifically in Reasoning Language Models (RLMs), is the ability for an artificial neural network to provide top-down feedback to its input or previous layers, based on their outputs or subsequent layers. This process involves self-assessment and internal deliberation, aiming to enhance reasoning accuracy, minimize errors (like hallucinations), and increase interpretability. Reflection is a form of "test-time compute", where additional computational resources are used during inference.