arXiv:2607. 02369v1 Announce Type: cross Abstract: LLMs stage a new form of cultural encounter that is massive, automated, and monolingual.
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arXiv:2606. 28333v1 Announce Type: cross Abstract: \begin{quote} The biases in Large Language Models' (LLMs) outputs remain inadequately theorised, particularly from the perspective of the Global South.
arXiv:2607. 11808v1 Announce Type: cross Abstract: This paper proposes a human-centered artificial intelligence (HCAI) framework for AI-assisted lexicography.
The paper proposes a new way to evaluate language models on cultural understanding by focusing on interpretive depth rather than just factual recall. It argues that literary interpretation, where scholars can disagree yet still assess the quality of evidence, provides a useful framework for testing how models handle cultural references, reuse, and transformation across texts. The authors suggest linking evidence-centered benchmarks, preserving scholarly disagreement, and conducting model-development experiments on literary data, with Danish literature as a starting point for broader applications.
arXiv:2607. 06544v1 Announce Type: new Abstract: As Artificial Intelligence (AI) makes inroads into different parts of the Indian subcontinent, there is significant interest in studying how AI impacts the linguistic and cultural foundations of this civilization.
arXiv:2607. 01776v1 Announce Type: cross Abstract: In the age of AI, what will be good knowledge?
The paper explores how "culture" can be operationalised in Natural Language Processing (NLP) and what this reveals about the possibilities and limits of considering a plurality of cultural backgrounds in technological design. It proposes that cultural alignment cannot be achieved only by adding more examples of "other cultures", rather it requires plural epistemologies: allowing multiple, locally grounded ways of knowing.