PoliticsBench: Benchmarking Political Values in Large Language Models with Multi-Turn Roleplay
While Large Language Models (LLMs) are increasingly used as primary sources of information, their potential for political bias may impact their objectivity. Existing benchmarks of LLM social bias primarily evaluate demographic stereotypes, and when political bias is measured, it is done so at a coarse level, overlooking the values that shape sociopolitical reasoning. We introduce PoliticsBench, a multi-stage roleplay benchmark for evaluating fine-grained value expression in LLMs. Across twenty evolving scenarios, models articulate tradeoffs, take positions, and make decisions under competing pressures. Across eight prominent LLMs, we show that scenario-based prompting elicits broader and ...
| Authors | Rohan Khetan, Ashna Khetan |
|---|---|
| Primary category | cs.CL |
| Published | 25 March 2026 |
| Last updated at source | 2 June 2026 |
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