# A Survey on Large Language Models with Multilingualism: Recent Advances and New Frontiers

arXiv: https://arxiv.org/abs/2405.10936 · HTML: https://mlsanity.com/paper/2405.10936/

## Key facts

- Cited by 40 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 May 2024.

## Built on by (most cited first, 30 of 40)

- [Parameter-Efficient Fine-Tuning in Large Models: A Survey of Methodologies](https://mlsanity.com/paper/2410.19878/) (2024)
- [The State of Multilingual LLM Safety Research: From Measuring the Language Gap to Mitigating It](https://mlsanity.com/paper/2505.24119/) (2025)
- [Multilingual Blending: LLM Safety Alignment Evaluation with Language Mixture](https://mlsanity.com/paper/2407.07342/) (2024)
- [A Survey of Conversational Search](https://mlsanity.com/paper/2410.15576/) (2024)
- [Think Natively: Unlocking Multilingual Reasoning with Consistency-Enhanced Reinforcement Learning](https://mlsanity.com/paper/2510.07300/) (2025)
- [GPT-4o: Visual perception performance of multimodal large language models in piglet activity understanding](https://mlsanity.com/paper/2406.09781/) (2024)
- [Fast and Cost-effective Speculative Edge-Cloud Decoding with Early Exits](https://mlsanity.com/paper/2505.21594/) (2025)
- [Applications of Large Models in Medicine](https://mlsanity.com/paper/2502.17132/) (2025)
- [Multilingual Prompt Engineering in Large Language Models: A Survey Across NLP Tasks](https://mlsanity.com/paper/2505.11665/) (2025)
- [DEPT: Decoupled Embeddings for Pre-training Language Models](https://mlsanity.com/paper/2410.05021/) (2024)
- [DCAD-2000: A Multilingual Dataset across 2000+ Languages with Data Cleaning as Anomaly Detection](https://mlsanity.com/paper/2502.11546/) (2025)
- [Massively Multilingual Adaptation of Large Language Models Using Bilingual Translation Data](https://mlsanity.com/paper/2506.00469/) (2025)
- [Under the Shadow of Babel: How Language Shapes Reasoning in LLMs](https://mlsanity.com/paper/2506.16151/) (2025)
- [One Model, Many Morals: Uncovering Cross-Linguistic Misalignments in Computational Moral Reasoning](https://mlsanity.com/paper/2509.21443/) (2025)
- [Responsible Multilingual Large Language Models: A Survey of Development, Applications, and Societal Impact](https://mlsanity.com/paper/2410.17532/) (2024)
- [Evaluating Large Language Model with Knowledge Oriented Language Specific Simple Question Answering](https://mlsanity.com/paper/2505.16591/) (2025)
- [LinguaMap: Which Layers of LLMs Speak Your Language and How to Tune Them?](https://mlsanity.com/paper/2601.20009/) (2026)
- [Towards Safe Multilingual Frontier AI](https://mlsanity.com/paper/2409.13708/) (2024)
- [Large Vision-Language Models for Remote Sensing Visual Question Answering](https://mlsanity.com/paper/2411.10857/) (2024)
- [SASFT: Sparse Autoencoder-guided Supervised Finetuning to Mitigate Unexpected Code-Switching in LLMs](https://mlsanity.com/paper/2507.14894/) (2025)
- [SoT: Structured-of-Thought Prompting Guides Multilingual Reasoning in Large Language Models](https://mlsanity.com/paper/2510.02648/) (2025)
- [Multilingual Agent-Based World Modeling for Social Science](https://mlsanity.com/paper/2512.07195/) (2025)
- [Breaking Minds, Breaking Systems: Jailbreaking Large Language Models via Human-like Psychological Manipulation](https://mlsanity.com/paper/2512.18244/) (2025)
- [Mitigating Translationese Bias in Multilingual LLM-as-a-Judge via Disentangled Information Bottleneck](https://mlsanity.com/paper/2603.10351/) (2026)
- [A Comparative Study of Translation Bias and Accuracy in Multilingual Large Language Models for Cross-Language Claim Verification](https://mlsanity.com/paper/2410.10303/) (2024)
- [Generating Medically-Informed Explanations for Depression Detection using LLMs](https://mlsanity.com/paper/2503.14671/) (2025)
- [Can Smaller Large Language Models Evaluate Research Quality?](https://mlsanity.com/paper/2508.07196/) (2025)
- [Benchmarking Open-Source Large Language Models for Persian in Zero-Shot and Few-Shot Learning](https://mlsanity.com/paper/2510.12807/) (2025)
- [Sentra-Guard: A Real-Time Multilingual Defense Against Adversarial LLM Prompts](https://mlsanity.com/paper/2510.22628/) (2025)
- [From Utterance to Vividity: Training Expressive Subtitle Translation LLM via Adaptive Local Preference Optimization](https://mlsanity.com/paper/2602.01068/) (2026)

## Abstract (arXiv)

The rapid development of Large Language Models (LLMs) demonstrates remarkable multilingual capabilities in natural language processing, attracting global attention in both academia and industry. To mitigate potential discrimination and enhance the overall usability and accessibility for diverse language user groups, it is important for the development of language-fair technology. Despite the breakthroughs of LLMs, the investigation into the multilingual scenario remains insufficient, where a comprehensive survey to summarize recent approaches, developments, limitations, and potential solutions is desirable. To this end, we provide a survey with multiple perspectives on the utilization of LLMs in the multilingual scenario. We first rethink the transitions between previous and current research on pre-trained language models. Then we introduce several perspectives on the multilingualism of LLMs, including training and inference methods, information retrieval, model security, multi-domain with language culture, and usage of datasets. We also discuss the major challenges that arise in these aspects, along with possible solutions. Besides, we highlight future research directions that aim at further enhancing LLMs with multilingualism. The survey aims to help the research community address multilingual problems and provide a comprehensive understanding of the core concepts, key techniques, and latest developments in multilingual natural language processing based on LLMs.