Concept

Preference for Divergence-Based Objective Functions

In designing objective functions, a structure that represents the difference between two probability distributions is often preferred. This form is conceptually advantageous because it can be interpreted as a divergence, which measures the 'distance' or difference between the two distributions. This contrasts with less ideal forms, such as the difference between a log-probability distribution and another arbitrary function, which lack this clear interpretation.

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Updated 2026-01-15

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Ch.4 Alignment - Foundations of Large Language Models

Foundations of Large Language Models

Foundations of Large Language Models Course

Computing Sciences

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