Work

Democratic or Authoritarian? Probing a New Dimension of Political Biases in Large Language Models

Year: 2026

Type: conference-paper

Abstract: David Guzman Piedrahita, Irene Strauss, Rada Mihalcea, Zhijing Jin. Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers). 2026.

Source: Conference of the European Chapter of the Association for Computational Linguistics

DOI: 10.18653/v1/2026.eacl-long.27

Authors: David Guzman Piedrahita, Irene Strauss, Rada Mihalcea, Zhijing Jin

Institutions: University of Zurich, ETH Zurich, University of Michigan, University of Toronto

Language: English

Topic: Ethics and Social Impacts of AI

Subfield: Safety Research

Field: Social Sciences

Domain: Social Sciences

Open Access status: hybrid

Funders: National Science Foundation, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Bundesministerium für Bildung und Forschung, Natural Sciences and Engineering Research Council of Canada

Awards: Representation Learning for Arbitrarily Long Richly Formatted Multimedia Documents, G1796699909, Verbundprojekt TUEAI: Tübingen AI Center, G4980694453, SCH: Natural Language Processing for Enhanced Behavioral Counseling

OpenAlex ID: W7140124564

FWCI: 9.664

Cites:

Cited by: 1

Related to: 10