cs.CLMar 16, 2026

Information Asymmetry across Language Varieties: A Case Study on Cantonese-Mandarin and Bavarian-German QA

Authors: Renhao Pei, Siyao Peng, Verena Blaschke, Robert Litschko, Barbara Plank

Organizations: MaiNLP, Center for Information and Language Processing, LMU Munich, Germany · Munich Center for Machine Learning (MCML), Germany · ELLIS Institute Finland · University of Turku, Finland

Abstract

Large Language Models (LLMs) are becoming a common way for humans to seek knowledge, yet their coverage and reliability vary widely. Especially for local language varieties, there are large asymmetries, e.g., information in local Wikipedia that is absent from the standard variant. However, little is known about how well LLMs perform under such information asymmetry, especially on closely related languages. We manually construct a novel challenge question-answering (QA) dataset that captures knowledge conveyed on a local Wikipedia page, which is absent from their higher-resource counterparts-covering Mandarin Chinese vs. Cantonese and German vs. Bavarian. Our experiments show that LLMs fail to answer questions about information only in local editions of Wikipedia. Providing context from lead sections substantially improves performance, with further gains possible via translation. Our topical, geographic annotations, and stratified evaluations reveal the usefulness of local Wikipedia editions as sources of both regional and global information. These findings raise critical questions about inclusivity and cultural coverage of LLMs.

Figures & tables

Appendix figures & tables5 assets

Supplementary material from the paper’s appendix.

Appendix

Explore similar work

CardsList
  1. Leveraging Wikidata for Geographically Informed Sociocultural Bias Dataset Creation: Application to Latin America

    Feb 16, 2026Yannis Karmim, Renato Pino, Hernan Contreras +6Cultural Bias in Language ModelsCultural Knowledge in Language Models

  2. Location Not Found: Exposing Implicit Local and Global Biases in Multilingual LLMs

    Apr 21, 2026Guy Mor-Lan, Omer Goldman, Matan Eyal +6Multilingual Language ModelsMultilingual Language Model Evaluation

  3. When English Rewrites Local Knowledge: Global Narrative Dominance in Large Language Models

    May 28, 2026Md Arid Hasan, Ruwad Naswan, Farhan Samir +2Multilingual Language Model EvaluationLLM Grounding