Multilingual Education and Policy

Neueste Paper

• AI systems and the reproduction of (standard) language ideologies in World Englishes

  Kingsley Ugwuanyi · 31. Juli 2026

  The rapid growth of large language models (LLMs) has resurrected age-old questions in sociolinguistics and world Englishes, such as who decides what counts as legitimate English, whose English is suspect etc. This paper examines how AI systems, their uses and discourse on them reflect, reinforce, an…

• Generative AI and linguistic diversity in academic writing and publishing: Perspectives from World Englishes

  Kingsley Ugwuanyi, Christian Mair, Sender Dovchin, Iker Erdocia, Maria Kuteeva, Esther Airemionkhale · 31. Juli 2026

  The rise of generative artificial intelligence (GenAI) in academic writing and publishing (AWP) raises questions about linguistic inclusivity and the legitimacy of diverse Englishes in global scholarly communication. This article responds to these questions through a structured scholarly dialogue in…

• Evaluating Regional Bias in LLMs From Abstract Stereotype to Concrete Social Decision-Making

  Jiayuan Di, Haoyi Yang, Yufei Luo, Jiahui Qu, Yiming Wang · 30. Juli 2026

  Regional bias in large language models (LLMs) may shape both perceptions of regional groups and decisions about individuals from different regions. Yet existing studies often examine these manifestations separately, leaving their structure and consequences unclear. We introduce Stereotypes-to-Decisi…

• CARTE: A Benchmark for Mapping Language Model Knowledge Across France

  Sarah Almeida Carneiro, Christos Xypolopoulos, Xiao Fei, Yang Zhang, Michalis Vazirgiannis · 2. Juni 2026

  We introduce CARTE 1 (Culturally Anchored Regional-Territorial Evaluation), a multiplechoice benchmark for evaluating the ability of large language models (LLMs) to perform fine-grained reasoning over geographically grounded and regionally differentiated knowledge within France. While prior benchmar…

• \textit{Versteasch du mi?} Computational and Socio-Linguistic Perspectives on GenAI, LLMs, and Non-Standard Language

  Verena Platzgummer, John McCrae, Sina Ahmadi · 31. März 2026

  The design of Large Language Models (LLMs) and generative artificial intelligence (GenAI) has been shown to be "unfair" to less-spoken languages (Petrov et al., 2023) and to deepen the digital language divide (Bella et al., 2023). Critical sociolinguistic work has also argued that these technologies…

• Triangulating Temporal Dynamics in Multilingual Swiss Online News

  Bros Victor, Dufraisse Evan, Popescu Adrian, Gatica-Perez Daniel · 24. März 2026

  Analyzing news coverage in multilingual societies can offer valuable insights into the dynamics of public discourse and the development of collective narratives, yet comprehensive studies that account for linguistic and cultural diversity within national media ecosystems remain limited, particularly…

• Stylistic Evolution and LLM Neutrality in Singlish Language

  Linus Tze En Foo, Weihan Angela Ng, Wenkai Li, Lynnette Hui Xian Ng · 13. Januar 2026

  Singlish is a creole rooted in Singapore's multilingual environment that continues to evolve alongside social and technological change. We examine diachronic stylistic change across a decade of informal digital messages and ask whether Large Language Models (LLMs) can generate temporally neutral out…

• Modeling Topics and Sociolinguistic Variation in Code-Switched Discourse: Insights from Spanish-English and Spanish-Guaraní

  Nemika Tyagi, Nelvin Licona Guevara, Olga Kellert · 4. Dezember 2025

  This study presents an LLM-assisted annotation pipeline for the sociolinguistic and topical analysis of bilingual discourse in two typologically distinct contexts: Spanish-English and Spanish-Guaraní. Using large language models, we automatically labeled topic, genre, and discourse-pragmatic functio…

• Exploring Performance Variations in Finetuned Translators of Ultra-Low Resource Languages: Do Linguistic Differences Matter?

  Isabel Gon\c{c}alves, Paulo Cavalin, Claudio Pinhanez · 1. Dezember 2025

  Finetuning pre-trained language models with small amounts of data is a commonly-used method to create translators for ultra-low resource languages such as endangered Indigenous languages. However, previous works have reported substantially different performances with translators created using simila…