# Culturally Aware and Adapted NLP: A Taxonomy and a Survey of the State of the Art

arXiv: https://arxiv.org/abs/2406.03930 · HTML: https://mlsanity.com/paper/2406.03930/

## Key facts

- Cited by 26 papers in the map (data through 14 Oct 2026).
- Builds on 178 of its 322 references that are in the map.
- First posted on arXiv 6 Jun 2024.

## Builds on (most cited first, 30 of 178)

- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [Training language models to follow instructions with human feedback](https://mlsanity.com/paper/2203.02155/) (2022)
- [LoRA: Low-Rank Adaptation of Large Language Models](https://mlsanity.com/paper/2106.09685/) (2021)
- [Direct Preference Optimization: Your Language Model is Secretly a Reward Model](https://mlsanity.com/paper/2305.18290/) (2023)
- [Measuring Massive Multitask Language Understanding](https://mlsanity.com/paper/2009.03300/) (2020)
- [GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding](https://mlsanity.com/paper/1804.07461/) (2018)
- [Parameter-Efficient Transfer Learning for NLP](https://mlsanity.com/paper/1902.00751/) (2019)
- [Deep reinforcement learning from human preferences](https://mlsanity.com/paper/1706.03741/) (2017)
- [Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback](https://mlsanity.com/paper/2204.05862/) (2022)
- [Constitutional AI: Harmlessness from AI Feedback](https://mlsanity.com/paper/2212.08073/) (2022)
- [mT5: A massively multilingual pre-trained text-to-text transformer](https://mlsanity.com/paper/2010.11934/) (2020)
- [Don't Stop Pretraining: Adapt Language Models to Domains and Tasks](https://mlsanity.com/paper/2004.10964/) (2020)
- [ConceptNet 5.5: An Open Multilingual Graph of General Knowledge](https://mlsanity.com/paper/1612.03975/) (2016)
- [A General Language Assistant as a Laboratory for Alignment](https://mlsanity.com/paper/2112.00861/) (2021)
- [HyperNetworks](https://mlsanity.com/paper/1609.09106/) (2016)
- [Semantics derived automatically from language corpora contain human-like biases](https://mlsanity.com/paper/1608.07187/) (2016)
- [Whose Opinions Do Language Models Reflect?](https://mlsanity.com/paper/2303.17548/) (2023)
- [Out of One, Many: Using Language Models to Simulate Human Samples](https://mlsanity.com/paper/2209.06899/) (2022)
- [CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked Language Models](https://mlsanity.com/paper/2010.00133/) (2020)
- [Using Large Language Models to Simulate Multiple Humans and Replicate Human Subject Studies](https://mlsanity.com/paper/2208.10264/) (2022)
- [CMMLU: Measuring massive multitask language understanding in Chinese](https://mlsanity.com/paper/2306.09212/) (2023)
- [MAD-X: An Adapter-Based Framework for Multi-Task Cross-Lingual Transfer](https://mlsanity.com/paper/2005.00052/) (2020)
- [Towards Measuring the Representation of Subjective Global Opinions in Language Models](https://mlsanity.com/paper/2306.16388/) (2023)
- [Toxicity in ChatGPT: Analyzing Persona-assigned Language Models](https://mlsanity.com/paper/2304.05335/) (2023)
- [XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning](https://mlsanity.com/paper/2005.00333/) (2020)
- [K-Adapter: Infusing Knowledge into Pre-Trained Models with Adapters](https://mlsanity.com/paper/2002.01808/) (2020)
- [Social Simulacra: Creating Populated Prototypes for Social Computing Systems](https://mlsanity.com/paper/2208.04024/) (2022)
- [Mitigating Gender Bias in Natural Language Processing: Literature Review](https://mlsanity.com/paper/1906.08976/) (2019)
- [Annotators with Attitudes: How Annotator Beliefs And Identities Bias Toxic Language Detection](https://mlsanity.com/paper/2111.07997/) (2021)
- [Social Chemistry 101: Learning to Reason about Social and Moral Norms](https://mlsanity.com/paper/2011.00620/) (2020)

## Built on by (most cited first, 26 of 26)

- [Survey of Cultural Awareness in Language Models: Text and Beyond](https://mlsanity.com/paper/2411.00860/) (2024)
- [CaLMQA: Exploring culturally specific long-form question answering across 23 languages](https://mlsanity.com/paper/2406.17761/) (2024)
- [Tiny Aya: Bridging Scale and Multilingual Depth](https://mlsanity.com/paper/2603.11510/) (2026)
- [From Surveys to Narratives: Rethinking Cultural Value Adaptation in LLMs](https://mlsanity.com/paper/2505.16408/) (2025)
- [SaudiCulture: A Benchmark for Evaluating Large Language Models Cultural Competence within Saudi Arabia](https://mlsanity.com/paper/2503.17485/) (2025)
- [DARE: Diverse Visual Question Answering with Robustness Evaluation](https://mlsanity.com/paper/2409.18023/) (2024)
- [Steering LLMs for Culturally Localized Generation](https://mlsanity.com/paper/2603.23301/) (2026)
- [Evaluating Large Language Model with Knowledge Oriented Language Specific Simple Question Answering](https://mlsanity.com/paper/2505.16591/) (2025)
- [Crossroads of Continents: Automated Artifact Extraction for Cultural Adaptation with Large Multimodal Models](https://mlsanity.com/paper/2407.02067/) (2024)
- [CultureMERT: Continual Pre-Training for Cross-Cultural Music Representation Learning](https://mlsanity.com/paper/2506.17818/) (2025)
- [CALM: Culturally Self-Aware Language Models](https://mlsanity.com/paper/2601.03483/) (2026)
- [A Unified Framework to Quantify Cultural Intelligence of AI](https://mlsanity.com/paper/2603.01211/) (2026)
- [Anthropogenic Regional Adaptation in Multimodal Vision-Language Model](https://mlsanity.com/paper/2604.11490/) (2026)
- [The Culture Funnel: You Can't Align What isn't in the Data](https://mlsanity.com/paper/2606.13808/) (2026)
- [Towards culturally-appropriate conversational AI for health in the majority world: An exploratory study with citizens and professionals in Latin America](https://mlsanity.com/paper/2507.01719/) (2025)
- [BengaliMoralBench: A Benchmark for Auditing Moral Reasoning in Large Language Models within Bengali Language and Culture](https://mlsanity.com/paper/2511.03180/) (2025)
- [Kinship Data Benchmark for Multi-hop Reasoning](https://mlsanity.com/paper/2601.07794/) (2026)
- [Text-to-Image Models and Their Representation of People from Different Nationalities Engaging in Activities](https://mlsanity.com/paper/2504.06313/) (2025)
- [Against 'softmaxing' culture](https://mlsanity.com/paper/2506.22968/) (2025)
- [Towards Cross-lingual Values Judgment: A Consensus-Pluralism Perspective](https://mlsanity.com/paper/2602.17283/) (2026)
- [Density-Guided Response Optimization: Community-Grounded Alignment via Implicit Acceptance Signals](https://mlsanity.com/paper/2603.03242/) (2026)
- [Pragmatics Meets Culture: Culturally-adapted Artwork Description Generation and Evaluation](https://mlsanity.com/paper/2604.02557/) (2026)
- [Culture-Aware Humorous Captioning: Multimodal Humor Generation across Cultural Contexts](https://mlsanity.com/paper/2604.18091/) (2026)
- [Modeling Community Attitude through Reaction Tone: A Human-AI Collaborative Framework for Evaluating LLM Alignment with Linguistic Behaviors in Online Communities](https://mlsanity.com/paper/2605.27388/) (2026)
- [ExCAM: Explainable Cultural Awareness Metrics](https://mlsanity.com/paper/2605.29897/) (2026)
- [PAUSE: Editable Strategy Artifacts for Long-Form Cultural Story Adaptation](https://mlsanity.com/paper/2608.28633/) (2026)

## Abstract (arXiv)

The surge of interest in "culture" in NLP has inspired much recent research, but a shared understanding of "culture" remains unclear, making it difficult to evaluate progress in this emerging area. Drawing on prior research in NLP and related fields, we propose a fine-grained taxonomy of elements in culture that can provide a systematic framework for analyzing and understanding research progress. Using the taxonomy, we survey existing resources and methods for culturally aware and adapted NLP, providing an overview of the state of the art and the research gaps that still need to be filled.