We present a survey of more than 90 recent papers that aim to study cultural representation
and inclusion in large language models (LLMs). We observe that none of the studies …

To enhance language models' cultural awareness, we design a generalizable pipeline to
construct cultural knowledge bases from different online communities on a massive scale …

Large language models (LLMs) are used for long-form question answering (LFQA), which
requires them to generate paragraph-length answers to complex questions. While LFQA has …

The surge of interest in culturally aware and adapted Natural Language Processing (NLP)
has inspired much recent research. However, the lack of common understanding of the …

To create culturally inclusive vision-language models (VLMs), the foremost requirement is
developing a test benchmark that can diagnose the models' ability to respond to questions …

Large-scale deployment of large language models (LLMs) in various applications, such as
chatbots and virtual assistants, requires LLMs to be culturally sensitive to the user to ensure …

Large language models (LLMs) often lack culture-specific knowledge of daily life, especially
across diverse regions and non-English languages. Existing benchmarks for evaluating …

Code-switching (CS), a phenomenon where multilingual speakers alternate between
languages in a discourse, can convey subtle cultural and linguistic nuances that can be …

Influential and popular benchmarks in AI are largely irrelevant to developing NLP tools for
low-resource, Indigenous languages. With the primary goal of measuring the performance of …