# XLM-K: Improving Cross-Lingual Language Model Pre-training with Multilingual Knowledge

arXiv: https://arxiv.org/abs/2109.12573 · HTML: https://mlsanity.com/paper/2109.12573/

## Key facts

- Cited by 18 papers in the map (data through 14 Oct 2026).
- Builds on 39 of its 51 references that are in the map.
- First posted on arXiv 26 Sep 2021.

## Builds on (most cited first, 30 of 39)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [A Simple Framework for Contrastive Learning of Visual Representations](https://mlsanity.com/paper/2002.05709/) (2020)
- [Momentum Contrast for Unsupervised Visual Representation Learning](https://mlsanity.com/paper/1911.05722/) (2019)
- [SQuAD: 100,000+ Questions for Machine Comprehension of Text](https://mlsanity.com/paper/1606.05250/) (2016)
- [Unsupervised Cross-lingual Representation Learning at Scale](https://mlsanity.com/paper/1911.02116/) (2019)
- [Language Models as Knowledge Bases?](https://mlsanity.com/paper/1909.01066/) (2019)
- [Cross-lingual Language Model Pretraining](https://mlsanity.com/paper/1901.07291/) (2019)
- [ConceptNet 5.5: An Open Multilingual Graph of General Knowledge](https://mlsanity.com/paper/1612.03975/) (2016)
- [XNLI: Evaluating Cross-lingual Sentence Representations](https://mlsanity.com/paper/1809.05053/) (2018)
- [CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data](https://mlsanity.com/paper/1911.00359/) (2019)
- [ERNIE: Enhanced Language Representation with Informative Entities](https://mlsanity.com/paper/1905.07129/) (2019)
- [KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation](https://mlsanity.com/paper/1911.06136/) (2019)
- [MLQA: Evaluating Cross-lingual Extractive Question Answering](https://mlsanity.com/paper/1910.07475/) (2019)
- [K-Adapter: Infusing Knowledge into Pre-Trained Models with Adapters](https://mlsanity.com/paper/2002.01808/) (2020)
- [K-BERT: Enabling Language Representation with Knowledge Graph](https://mlsanity.com/paper/1909.07606/) (2019)
- [InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training](https://mlsanity.com/paper/2007.07834/) (2020)
- [XGLUE: A New Benchmark Dataset for Cross-lingual Pre-training, Understanding and Generation](https://mlsanity.com/paper/2004.01401/) (2020)
- [A Survey Of Cross-lingual Word Embedding Models](https://mlsanity.com/paper/1706.04902/) (2017)
- [Multilingual LAMA: Investigating Knowledge in Multilingual Pretrained Language Models](https://mlsanity.com/paper/2102.00894/) (2021)
- [X-FACTR: Multilingual Factual Knowledge Retrieval from Pretrained Language Models](https://mlsanity.com/paper/2010.06189/) (2020)
- [Pretrained Encyclopedia: Weakly Supervised Knowledge-Pretrained Language Model](https://mlsanity.com/paper/1912.09637/) (2019)
- [Entities as Experts: Sparse Memory Access with Entity Supervision](https://mlsanity.com/paper/2004.07202/) (2020)
- [Unicoder: A Universal Language Encoder by Pre-training with Multiple Cross-lingual Tasks](https://mlsanity.com/paper/1909.00964/) (2019)
- [ERNIE-M: Enhanced Multilingual Representation by Aligning Cross-lingual Semantics with Monolingual Corpora](https://mlsanity.com/paper/2012.15674/) (2020)
- [Grounded Conversation Generation as Guided Traverses in Commonsense Knowledge Graphs](https://mlsanity.com/paper/1911.02707/) (2019)
- [Knowledge-Aware Language Model Pretraining](https://mlsanity.com/paper/2007.00655/) (2020)
- [Explicit Alignment Objectives for Multilingual Bidirectional Encoders](https://mlsanity.com/paper/2010.07972/) (2020)

## Built on by (most cited first, 18 of 18)

- [Retrieving Multimodal Information for Augmented Generation: A Survey](https://mlsanity.com/paper/2303.10868/) (2023)
- [EASE: Entity-Aware Contrastive Learning of Sentence Embedding](https://mlsanity.com/paper/2205.04260/) (2022)
- [Beneath the Surface of Consistency: Exploring Cross-lingual Knowledge Representation Sharing in LLMs](https://mlsanity.com/paper/2408.10646/) (2024)
- [mLUKE: The Power of Entity Representations in Multilingual Pretrained Language Models](https://mlsanity.com/paper/2110.08151/) (2021)
- [Enhancing Multilingual Language Model with Massive Multilingual Knowledge Triples](https://mlsanity.com/paper/2111.10962/) (2021)
- [Federated Multilingual Models for Medical Transcript Analysis](https://mlsanity.com/paper/2211.09722/) (2022)
- [Leveraging Knowledge in Multilingual Commonsense Reasoning](https://mlsanity.com/paper/2110.08462/) (2021)
- [EntityCS: Improving Zero-Shot Cross-lingual Transfer with Entity-Centric Code Switching](https://mlsanity.com/paper/2210.12540/) (2022)
- [Machine-Created Universal Language for Cross-lingual Transfer](https://mlsanity.com/paper/2305.13071/) (2023)
- [Understanding LLMs' Cross-Lingual Context Retrieval: How Good It Is And Where It Comes From](https://mlsanity.com/paper/2504.10906/) (2025)
- [Personalized Query Auto-Completion for Long and Short-Term Interests with Adaptive Detoxification Generation](https://mlsanity.com/paper/2505.20966/) (2025)
- [A Survey on Knowledge-Enhanced Pre-trained Language Models](https://mlsanity.com/paper/2212.13428/) (2022)
- [Modeling Sequential Sentence Relation to Improve Cross-lingual Dense Retrieval](https://mlsanity.com/paper/2302.01626/) (2023)
- [In What Languages are Generative Language Models the Most Formal? Analyzing Formality Distribution across Languages](https://mlsanity.com/paper/2302.12299/) (2023)
- [mPMR: A Multilingual Pre-trained Machine Reader at Scale](https://mlsanity.com/paper/2305.13645/) (2023)
- [LEIA: Facilitating Cross-lingual Knowledge Transfer in Language Models with Entity-based Data Augmentation](https://mlsanity.com/paper/2402.11485/) (2024)
- [UniPSDA: Unsupervised Pseudo Semantic Data Augmentation for Zero-Shot Cross-Lingual Natural Language Understanding](https://mlsanity.com/paper/2406.16372/) (2024)
- [CroPS: Improving Dense Retrieval with Cross-Perspective Positive Samples in Short-Video Search](https://mlsanity.com/paper/2511.15443/) (2025)

## Abstract (arXiv)

Cross-lingual pre-training has achieved great successes using monolingual and bilingual plain text corpora. However, most pre-trained models neglect multilingual knowledge, which is language agnostic but comprises abundant cross-lingual structure alignment. In this paper, we propose XLM-K, a cross-lingual language model incorporating multilingual knowledge in pre-training. XLM-K augments existing multilingual pre-training with two knowledge tasks, namely Masked Entity Prediction Task and Object Entailment Task. We evaluate XLM-K on MLQA, NER and XNLI. Experimental results clearly demonstrate significant improvements over existing multilingual language models. The results on MLQA and NER exhibit the superiority of XLM-K in knowledge related tasks. The success in XNLI shows a better cross-lingual transferability obtained in XLM-K. What is more, we provide a detailed probing analysis to confirm the desired knowledge captured in our pre-training regimen. The code is available at https://github.com/microsoft/Unicoder/tree/master/pretraining/xlmk.