Published November 5, 2025 | Version v1

Compression Decay Comprehension Test: An Information-Theoretic Benchmark for Measuring Machine Comprehension

Authors/Creators

Description

Abstract:
This paper introduces the Compression Decay Comprehension Test (CDCT), an information-theoretic framework for quantifying model comprehension through semantic robustness under compression. CDCT measures how language models preserve conceptual integrity when information density is systematically reduced, revealing nonlinear comprehension decay patterns independent of model scale. The framework provides a reproducible benchmark for identifying reasoning-aligned architectures, differentiating genuine comprehension from statistical mimicry.

Notes:
This version is the author’s original manuscript released for open access and citation.

An interactive dashboard summarizing the key metrics and trends from these experiments is available here: https://cdct-web-ranking.onrender.com/.

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Additional details

Dates

Submitted
2025-10-27

Software

Repository URL
https://github.com/rb125/cdct_framework
Programming language
Python
Development Status
Active