works on

From the 1 of 7 linked papers with an AI index.

most citedMulti-Agent Strategic Games with LLMs

1 citations · 1 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CY2026

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

Maxim Chupilkin

The paper estimates the geopolitical leanings of several large language models by applying a dynamic ordinal ideal‑point model to their simulated votes on 5,555 UN General Assembly…

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

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.GT20261 cited

Multi-Agent Strategic Games with LLMs

Maxim Chupilkin

This paper asks whether large language models (LLMs) can be used to study the strategic foundations of conflict and cooperation. I introduce LLMs as experimental subjects in a repe…

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…