Templated or fully synthetic? Prompt construction as a confound in measuring LLM political stance beyond writing assistance
Political stance detection in LLMs has long been dominated by closed-ended, multiple-choice political survey questions---originally designed for humans, and thus lacks the realism and nuance of human-AI interactions in the wild, while also being susceptible to sandbagging. The recent IssueBench framework substantially mitigates these limitations with templated prompts anchored in real-world chat logs. Given the rise in non-work-related use of GenAI assistants, we extend IssueBench beyond writing assistance to include two additional tasks, information seeking and opinion sharing. We argue that templated prompts still lack the nuance of real ones, especially for open-ended tasks, and remain...
| Authors | Ilias Chalkidis |
|---|---|
| Primary category | cs.CL |
| Published | 11 August 2026 |
| Last updated at source | 12 August 2026 |
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