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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.
The chapter discusses how large language models (LLMs) simplify the transformation of cultural material into analyzable variables and how LLM-driven agentic systems broaden machine assistance across research workflows. It examines key aspects of this emerging paradigm and its broader implications, arguing that LLMs increase scale, methodological diversity, and delegation while largely preserving the fundamental logic that underpins cultural measurement and claim formation.
QQ is a language metadata toolkit designed for multilingual NLP research. It aggregates diverse language metadata into a graph of varieties, scripts, regions, identifiers, names, and relations, and offers access via a Python API, CLI, and browser explorer. The toolkit enables normalization of identifiers, metadata retrieval, relation traversal, and discovery of external resources containing a language, and is demonstrated through audits of the HuggingFace Hub, linking resources with different identifier systems, and generating reproducible language-reporting tables.
arXiv:2405.06818v2 Announce Type: replace Abstract: Natural Language Processing (NLP) for Ghana's 73 living indigenous languages remains deeply fragmented, under-resourced, and heavily skewed toward...
KULTURE Bench is a new evaluation framework created to assess language models within the Korean cultural context. It includes datasets of cultural news, idioms, and poetry and tests models at word, sentence, and paragraph levels for cultural comprehension and reasoning. Experiments with models trained on different corpora show that current models still lack deep understanding of Korean cultural texts.
arXiv:2608.30107v1 Announce Type: cross Abstract: Understanding which countries are represented in NLP datasets is essential for identifying gaps, targeting data collection, measuring progress, and i...