most citedMulti-Agent Strategic Games with LLMs

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cs.CY2026

White Men Without Degrees Receive the Lowest Ratings from Large Language Models

Maxim Chupilkin

White men without an undergraduate degree receive the lowest average ratings among eight gender-race-education groups in controlled large-language-model evaluations of credit, hiri…

cs.CY2026

Artificial Institutions: How Institutional Design Shapes LLM Simulations

Maxim Chupilkin

Artificial societies built from large language model (LLM) agents are becoming a practical research tool in economics, political science, sociology, and computer science. Most atte…

cs.CY2026

Estimating the Geopolitical Preferences of Large Language Models from United Nations Voting Data

Maxim Chupilkin

How should researchers measure the geopolitical preferences expressed by large language models (LLMs)? Existing audits commonly rely on surveys and simple tests, but international-…

cs.CY2026

Geopolitical alignment: Endorsement effects in large language models

Maxim Chupilkin

Large language models (LLMs) are increasingly used to summarize and evaluate policy-relevant information, but it remains unclear whether their judgments are implicitly shaped by ge…

cs.CY2026

Hidden Topics: Measuring Sensitive AI Beliefs with List Experiments

Maxim Chupilkin

How can researchers identify beliefs that large language models (LLMs) hide? As LLMs become more sophisticated and the prevalence of alignment faking increases, combined with their…

cs.CY2025

Left Leaning Models: How AI Evaluates Economic Policy?

Maxim Chupilkin

Would artificial intelligence (AI) cut interest rates or adopt conservative monetary policy? Would it deregulate or opt for a more controlled economy? As AI use by economic policym…

cs.CY2025

The Prompt War: How AI Decides on a Military Intervention

Maxim Chupilkin

Which factors determine AI's propensity to support military intervention? While the use of AI in high-stakes decision-making is growing exponentially, we still lack systematic anal…