Cogent Arts & Humanities

Large Language Models in Multilingual Contexts: Critical and Applied Linguistic Perspectives

Cogent Arts & Humanities is pleased to welcome you to submit your research to the Article Collection "Large Language Models in Multilingual Contexts: Critical and Applied Linguistic Perspectives ".

This Article Collection investigates large language models (LLMs) from critical and applied linguistic perspectives, with particular attention to multilingual contexts involving English, Chinese, and Arabic. It brings together research that investigates how LLMs reshape language use, linguistic analysis, and meaning-making across institutional, professional, and intercultural settings. Contributions may explore AI-generated discourse, multilingual language practices, and AI-mediated communication, as well as AI-assisted and human-in-the-loop translation as a form of linguistic and communicative practice. The Collection also welcomes work that examines linguistic evaluation and assessment, including questions of validity, reliability, fairness, and accountability in the analysis and use of AI-generated language.

By foregrounding cross-linguistic and sociocultural perspectives, the Collection addresses both the opportunities offered by LLMs—such as expanded access to multilingual resources and increased efficiency in professional language work—and the challenges they pose, including bias, domain mismatch, and the marginalization of minoritized varieties. Critical and discourse-analytic approaches are particularly encouraged to uncover how LLMs shape power relations, representation, and communicative norms across languages.

As LLMs are increasingly integrated into multilingual communication, translation, and institutional language practices, their linguistic and societal implications require systematic scholarly scrutiny. Choices related to training data, model design, and evaluation directly influence how languages are presented, which varieties are privileged, and how meaning is constructed and interpreted across contexts. In English, Chinese, Arabic, and other multilingual settings, these issues have significant consequences for accessibility, communicative equity, linguistic standards, and professional language practices, including translation and evaluation.

Applied and critical linguistic research can illuminate how LLMs reproduce or challenge existing hierarchies, biases, and norms, while also offering evidence-based insights into the conditions under which AI-generated language may be reliable, transparent, and contextually appropriate. By integrating empirical analyses with conceptual and critical perspectives, this Collection aims to support principled, linguistically informed, and culturally responsive engagement with LLMs, moving beyond ad hoc adoption toward analytically grounded understanding and responsible use.

Submissions may include, but are not limited to, the following themes:
This Article Collection is situated within the scope of Cogent Arts & Humanities, particularly linguistics, applied linguistics, and translation studies. We invite research-based and reflective contributions that address critical and applied linguistic analyses of LLMs in multilingual contexts. Submissions may include empirical studies, conceptual discussions, discourse-analytic investigations, case reports, or review articles.

While the primary focus of the Collection is linguistic analysis, related areas of inquiry may include AI-assisted and machine translation as linguistic practice, linguistic evaluation and assessment of AI-generated language, and intercultural communication in AI-mediated contexts. Authors are encouraged to engage with questions of language use, variation, meaning-making, representation, and power, and to situate their analyses within specific linguistic, cultural, or institutional settings. Contributions that critically examine multilingual data, underrepresented languages or varieties, and cross-linguistic differences in LLM performance are especially welcome.

Meet the Guest Advisors

Dr. Asma Alsahil is an Associate professor of applied linguistics at the College of languages and Translation at IMSIU, Riyadh, Saudi Arabia. She has published widely in ISI-indexed journals including CALL, System, Innovation in Language Learning and Teaching, and Assessing Writing. Her research interests include; computer assisted language learning, AI in Language Education, L2 writing, Feedback, and intercultural communication.

Prof. Safaa M. Abdelhalim is a professor of TESOL at Imam Mohammad Ibn Saud Islamic University. Her research focuses on second language acquisition, L2 writing, teacher cognition, and AI-supported language learning and teaching. She has published widely in journals such as Computer Assisted Language Learning, System, Language Learning & Technology, Language Teaching Research, and Humanities and Social Sciences Communications.

Dr. Zainab Alsuhaibani is an associate professor of Applied Linguistics at Imam Mohammad Ibn Saud Islamic University (IMSIU), Saudi Arabia. Her research interests include L2 writing feedback, computer-assisted language learning, pragmatic competence and pragmatic instruction, and language learning strategies. She has published in different WoS- and Scopus-indexed journals. Her last articles appeared in Computer Assisted Language Learning, Assessing Writing, and Sage Open.

The Guest Advisors declare no conflict of interest regarding this work.