Papers by Maximilian Kreutner

2 papers
Persona-driven Simulation of Voting Behavior in the European Parliament with Large Language Models (2026.findings-eacl)

Copied to clipboard

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)

Copied to clipboard

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.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations