Do Political Opinions Transfer Between Western Languages? An Analysis of Unaligned and Aligned Multilingual LLMs
Paper · 2026 · Franziska Weeber, Tanise Ceron and Sebastian Padó
Summary
This paper asks whether multilingual LLMs hold a single, shared set of political views across languages or separate views per language, as human survey data across European countries might suggest. The authors tested 15 instruction-tuned bi- or multilingual models in German, English, French, Spanish and Italian. They used ProbVAA, a set of voting-advice-application statements from Ceron et al. (2024). Following that framework, they first discarded models whose stances changed under prompt rewording, then compared the agreement patterns of the remaining models across languages and policy areas. To tell genuine transfer apart from coincidental agreement, they used DPO to push two models from different families toward left or right positions, training only on English party-manifesto data. They then re-evaluated all five languages and added an open-ended statement-generation check. Before alignment, the models showed hardly any significant differences between languages. After alignment, opinions moved in nearly the same way in every language. The authors conclude that political opinions spread across Western languages inside these models. This makes alignment to a specific language or culture difficult and calls for cross-lingual evaluation.
Key points
- The study covers 15 unaligned instruction-tuned MLLMs, mostly smaller models, in five Western European languages. Each model was screened for robustness before any opinion analysis.
- ProbVAA statements are grouped into eight policy issues. Four are left-coded (environmental protection, welfare state, liberal society, open foreign policy). The other four are right-coded: tighter migration policy, fiscal restraint, economic liberalism, and an emphasis on law and order.
- Political alignment used DPO with English manifestos only, applied to two models. The resulting left or right shift appeared almost evenly in all five languages, which supports the opinion-transfer hypothesis (H1) over separate per-language opinions (H2).
- The authors note several limitations:
- Only high-resource Western languages were tested.
- Evaluation is mostly closed-ended, with only a small open-ended check.
- Alignment was done in English only.
- Effects on general capabilities after alignment were not tested.
- Code is available at github.com/frawee/cross_lingual_opinion_transfer, and model responses and annotations are on OSF. The aligned models are deliberately not released because of misuse risk.
Institutions
Fields, topics and concepts
📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Computer Science · 16,667 worksArtificial Intelligence · 16,194 worksArts and Humanities · 16,039 worksLanguage and Linguistics · 15,891 worksSocial Sciences · 1,772 worksSafety Research · 543 works
🧭 Topics 2Research subjects and languages the work is about.Language models & pretraining · 3,320 worksMultilingual & cross-lingual NLP · 828 works
Cite
Cite as Franziska Weeber, Tanise Ceron and Sebastian Padó. 2026. Do Political Opinions Transfer Between Western Languages? An Analysis of Unaligned and Aligned Multilingual LLMs. Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers).
@inproceedings{weeber2026do,
title = {{Do Political Opinions Transfer Between Western Languages? An Analysis of Unaligned and Aligned Multilingual LLMs}},
author = {Franziska Weeber, Tanise Ceron and Sebastian Padó},
booktitle = {Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)},
year = {2026},
doi = {10.18653/v1/2026.eacl-long.14},
url = {https://doi.org/10.18653/v1/2026.eacl-long.14}
}References
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