Claude Opus 4.6 fabricates more answers on Global North AI contexts than Global South ones, creating an exploitable vulnerability in AI control monitors.
Assessing cross-cultural alignment between chatgpt and human societies: An empirical study
4 Pith papers cite this work, alongside 23 external citations. Polarity classification is still indexing.
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Multicultural multi-agent LLM systems exhibit substantially lower value diversity than human societies on the World Values Survey, with diversity uncorrelated to per-agent alignment and further reduced by agent interactions.
Survey organizes LLM trustworthiness into seven categories and 29 sub-categories, measures eight sub-categories on popular models, and finds that more aligned models generally score higher but with varying effectiveness.
LLMs exhibit persistent inertia in value orientations, with harm avoidance and fairness remaining skewed across persona prompts.
citing papers explorer
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Geographic Blind Spots in AI Control Monitors: A Cross-National Audit of Claude Opus 4.6
Claude Opus 4.6 fabricates more answers on Global North AI contexts than Global South ones, creating an exploitable vulnerability in AI control monitors.
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Beyond Alignment: Value Diversity as a Collective Property in Multicultural Agent Systems
Multicultural multi-agent LLM systems exhibit substantially lower value diversity than human societies on the World Values Survey, with diversity uncorrelated to per-agent alignment and further reduced by agent interactions.
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Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment
Survey organizes LLM trustworthiness into seven categories and 29 sub-categories, measures eight sub-categories on popular models, and finds that more aligned models generally score higher but with varying effectiveness.
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Inertia in Moral and Value Judgments of Large Language Models
LLMs exhibit persistent inertia in value orientations, with harm avoidance and fairness remaining skewed across persona prompts.