How desirable is alignment between LLMs and linguistically diverse human users?
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Abstract (arXiv)
We discuss how desirable it is that Large Language Models (LLMs) be able to adapt or align their language behavior with users who may be diverse in their language use. User diversity may come about among others due to i) age differences; ii) gender characteristics, and/or iii) multilingual experience, and associated differences in language processing and use. We consider potential consequences for usability, communication, and LLM development.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 5 of its 81 references that are in the map. First posted on arXiv 18 Feb 2025.
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References · 5
- 2023Large Language Model Alignment: A Surveycited by 243
- 2022Lifting the Curse of Multilinguality by Pre-training Modular Transformerscited by 146
- 2023Personalisation within bounds: A risk taxonomy and policy framework for the alignment of large language models with personalised feedbackcited by 87
- 2024Understanding User Experience in Large Language Model Interactionscited by 44
- 2024Investigating Gender Bias in Turkish Language Modelscited by 1
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- 2025On the Alignment of Large Language Models with Global Human Opinion
- 2023CDEval: A Benchmark for Measuring the Cultural Dimensions of Large Language Models
- 2024Unintended Impacts of LLM Alignment on Global Representation
- 2025Operationalizing Pluralistic Values in Large Language Model Alignment Reveals Trade-offs in Safety, Inclusivity, and Model Behavior
- 2024Evaluating and Mitigating Linguistic Discrimination in Large Language Models
- 2025Multilingual != Multicultural: Evaluating Gaps Between Multilingual Capabilities and Cultural Alignment in LLMs
- 2024Do Large Language Models Perform the Way People Expect? Measuring the Human Generalization Function