A statistically consistent measure of Semantic Variability using Language Models

• URL: http://arxiv.org/abs/2502.00507v2
• Date: Tue, 11 Feb 2025 16:39:55 GMT
• Title: A statistically consistent measure of Semantic Variability using Language Models
• Authors: Yi Liu,
• Abstract summary: We present a measure of semantic variability that is statistically consistent under mild assumptions. This measure, denoted as semantic spectral entropy, is a easy to implement algorithm that requires just off the shelf language models.
• Score: 3.4933610074113464
• License:
• Abstract: To address the issue of variability in the output generated by a language model, we present a measure of semantic variability that is statistically consistent under mild assumptions. This measure, denoted as semantic spectral entropy, is a easy to implement algorithm that requires just off the shelf language models. We put very few restrictions on the language models and we have shown in a clear simulation studies that such method can generate accurate metric despite randomness that arise from the language models.

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