Digital Pantheon: Simulating and Auditing Coalition Formation with LLM Agents

The formation of political coalitions is a complex negotiation driven by both concrete policy objectives and deep-seated ideological convictions. While Large Language Models (LLMs) open new avenues for computational political science, the neutrality and helpfulness biases instilled by Reinforcement Learning from Human Feedback (RLHF) prevent them from sustaining steadfast partisan behaviour. We present a multi-agent framework that reconciles factual grounding with ideological alignment by combin

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ethics.ai (16 July 2026), “Digital Pantheon: Simulating and Auditing Coalition Formation with LLM Agents,” evidence record 11783, https://ethics.ai/record/11783 (originally published by arXiv).

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