Comparative Alignment Responses to Semantic Stressors in Large Language Models A Case Study Using a Culturally Loaded Astronomical Term

Comparative Alignment Responses to Semantic Stressors in Large Language Models A Case Study Using a Culturally Loaded Astronomical Term | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 7 January 2026 V1 Latest version Share on Comparative Alignment Responses to Semantic Stressors in Large Language Models A Case Study Using a Culturally Loaded Astronomical Term Author : Trent Slade 0009-0002-4515-9237 [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.176780586.68037220/v1 68 views 47 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract This paper presents a comparative analysis of how different large language model (LLM) architectures respond to an identical, formally neutral scientific prompt containing a culturally loaded semantic stressor: the planetary name Uranus. Responses from two centrally hosted, highcapacity models (Grok and Claude) are compared against a locally deployed, heavily quantized llama3:70b-instruct-q2_K model. Rather than evaluating factual correctness alone, the analysis focuses on discourse stability, epistemic posture, rhetorical strategy, and abstraction behavior under representational constraint. The results demonstrate that identical semantic input elicits qualitatively distinct alignment reflexes, shaped by model architecture, training priorities, and deployment context. These differences highlight how quantization and alignment objectives influence not only accuracy, but also the philosophical and communicative behavior of language models under semantic pressure. Supplementary Material File (comparative alignment.pdf) Download 82.37 KB Information & Authors Information Version history V1 Version 1 07 January 2026 Copyright This work is licensed under a Creative Commons Attribution 4.0 International License Keywords alignment behavior artificial intelligence large language models model quantization semantic stress testing Authors Affiliations Trent Slade 0009-0002-4515-9237 [email protected] View all articles by this author Metrics & Citations Metrics Article Usage 68 views 47 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Trent Slade. Comparative Alignment Responses to Semantic Stressors in Large Language Models A Case Study Using a Culturally Loaded Astronomical Term. Authorea . 07 January 2026. DOI: https://doi.org/10.22541/au.176780586.68037220/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. 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