Papers by Maximilian Kreutner
Persona-driven Simulation of Voting Behavior in the European Parliament with Large Language Models (2026.findings-eacl)
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| Challenge: | Large Language Models exhibit a progressive left-leaning bias, but can also produce behavior that aligns with socioeconomic groups. |
| Approach: | They analyze whether persona prompting can accurately predict individual voting decisions . they find that they can simulate the voting behavior of European Parliament members reasonably well . |
| Outcome: | The proposed model can predict the voting behavior of European Parliament members reasonably well, with a weighted F1 score of approximately 0.793. |
QSTN: A Modular Framework for Robust Questionnaire Inference with Large Language Models (2026.eacl-demo)
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| Challenge: | Questionnaire-like prompts have become an important format to probe, assess, and utilize large language models (LLMs) |
| Approach: | They propose an open-source Python framework for generating responses from questionnaire-style prompts to support in-silico surveys and annotation tasks with large language models (LLMs). |
| Outcome: | The proposed framework can be used to generate responses from questionnaire-style prompts and to perform annotations on large language models. |