Alemetria: A Protocol for Auditing Interpretational Behavior in Large Language Models (Short Version)

Read full text
Authors: A. V. Blinkova
Cited by: 2
References: 1

Abstract

This record presents a condensed English version of Alemetria, a protocol for auditing interpretational behavior in large language models (LLMs). Alemetria shifts evaluation from direct output comparison to validation of the conditions under which comparison is methodologically permissible. The protocol is organized as a structured sequence (B0-B4) and introduces a rule prohibiting calculation when interpretational comparability or stability conditions are not satisfied. The method distinguishes between substantive agreement, false consensus, divergence, evasion, interpretational suppression, and instability under reformulation. This condensed version focuses on the formal logic of the protocol. For the full methodological specification, extended empirical data, case studies, and appendices, see the Russian preprint:https://doi.org/10.5281/zenodo.19674164

Fields of Study & Subjects

Explainable Artificial Intelligence (XAI) Advanced Causal Inference Techniques Topic Modeling

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
21 April 2026
Language
EN
Document type
Preprint