# Translating Across Cultures: LLMs for Intralingual Cultural Adaptation

arXiv: https://arxiv.org/abs/2406.14504 · HTML: https://mlsanity.com/paper/2406.14504/

## Key facts

- Cited by 16 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 26 references that are in the map.
- First posted on arXiv 20 Jun 2024.

## Builds on (most cited first, 7 of 7)

- [Llama 2: Open Foundation and Fine-Tuned Chat Models](https://mlsanity.com/paper/2307.09288/) (2023)
- [Towards Measuring the Representation of Subjective Global Opinions in Language Models](https://mlsanity.com/paper/2306.16388/) (2023)
- [Challenges and Strategies in Cross-Cultural NLP](https://mlsanity.com/paper/2203.10020/) (2022)
- [Assessing Cross-Cultural Alignment between ChatGPT and Human Societies: An Empirical Study](https://mlsanity.com/paper/2303.17466/) (2023)
- [Cultural Alignment in Large Language Models: An Explanatory Analysis Based on Hofstede's Cultural Dimensions](https://mlsanity.com/paper/2309.12342/) (2023)
- [Evaluating Style Transfer for Text](https://mlsanity.com/paper/1904.02295/) (2019)
- [CPopQA: Ranking Cultural Concept Popularity by LLMs](https://mlsanity.com/paper/2311.07897/) (2023)

## Built on by (most cited first, 16 of 16)

- [Crosslingual Reasoning through Test-Time Scaling](https://mlsanity.com/paper/2505.05408/) (2025)
- [Language-Specific Latent Process Hinders Cross-Lingual Performance](https://mlsanity.com/paper/2505.13141/) (2025)
- [Jawaher: A Multidialectal Dataset of Arabic Proverbs for LLM Benchmarking](https://mlsanity.com/paper/2503.00231/) (2025)
- [Cultural Adaptation of Menus: A Fine-Grained Approach](https://mlsanity.com/paper/2408.13534/) (2024)
- [PerCul: A Story-Driven Cultural Evaluation of LLMs in Persian](https://mlsanity.com/paper/2502.07459/) (2025)
- [Do Large Language Models Truly Understand Cross-cultural Differences?](https://mlsanity.com/paper/2512.07075/) (2025)
- [Multilingual Amnesia: On the Transferability of Unlearning in Multilingual LLMs](https://mlsanity.com/paper/2601.05641/) (2026)
- [Steering LLMs for Culturally Localized Generation](https://mlsanity.com/paper/2603.23301/) (2026)
- [XCR-Bench: Benchmarking Cross-Cultural Reasoning in LLMs via Culture-Specific Items and Hall's Triad](https://mlsanity.com/paper/2601.14063/) (2026)
- [Semantic Label Drift in Cross-Cultural Translation](https://mlsanity.com/paper/2510.25967/) (2025)
- [RetrieveGPT: Merging Prompts and Mathematical Models for Enhanced Code-Mixed Information Retrieval](https://mlsanity.com/paper/2411.04752/) (2024)
- [Distributional Open-Ended Evaluation of LLM Cultural Value Alignment Based on Value Codebook](https://mlsanity.com/paper/2604.06210/) (2026)
- [Collaborative Participatory Research with LLM Agents in South Asia: An Empirically-Grounded Methodological Initiative and Agenda from Field Evidence in Sri Lanka](https://mlsanity.com/paper/2411.08294/) (2024)
- [Designing LLMs for cultural sensitivity: Evidence from English-Japanese translation](https://mlsanity.com/paper/2509.11921/) (2025)
- [Agentic AI Translate: An Agentic Translator Prototype for Translation as Communication Design](https://mlsanity.com/paper/2605.17041/) (2026)
- [Cultural Fidelity in English-to-Hindi Translation: A Preservation-Fluency Frontier for Gender Recoverability](https://mlsanity.com/paper/2605.27654/) (2026)

## Abstract (arXiv)

LLMs are increasingly being deployed for multilingual applications and have demonstrated impressive translation capabilities between several low and high-resource languages. An aspect of translation that often gets overlooked is that of cultural adaptation, or modifying source culture references to suit the target culture. While specialized translation models still outperform LLMs on the machine translation task when viewed from the lens of correctness, they are not sensitive to cultural differences often requiring manual correction. LLMs on the other hand have a rich reservoir of cultural knowledge embedded within its parameters that can be potentially exploited for such applications. In this paper, we define the task of cultural adaptation and create an evaluation framework to evaluate the performance of modern LLMs for cultural adaptation and analyze their cross-cultural knowledge while connecting related concepts across different cultures. We also analyze possible issues with automatic adaptation. We hope that this task will offer more insight into the cultural understanding of LLMs and their creativity in cross-cultural scenarios.