mlsanityData to 14 Oct 2026

Cross-lingual Information Retrieval with BERT

arXiv 2004.13005 ↗First posted 24 Apr 2020cs.IR cs.CL cs.LGcited by 27

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Abstract (arXiv)

Multiple neural language models have been developed recently, e.g., BERT and XLNet, and achieved impressive results in various NLP tasks including sentence classification, question answering and document ranking. In this paper, we explore the use of the popular bidirectional language model, BERT, to model and learn the relevance between English queries and foreign-language documents in the task of cross-lingual information retrieval. A deep relevance matching model based on BERT is introduced and trained by finetuning a pretrained multilingual BERT model with weak supervision, using home-made CLIR training data derived from parallel corpora. Experimental results of the retrieval of Lithuanian documents against short English queries show that our model is effective and outperforms the competitive baseline approaches.

Key facts. Cited by 27 papers in the map (data through 14 Oct 2026). First posted on arXiv 24 Apr 2020.

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Citing papers per year: 2021: 11; 2022: 4; 2023: 5; 2024: 3; 2025: 3; 2026: 1.

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  1. 2022Transfer Learning Approaches for Building Cross-Language Dense Retrieval Modelscited by 36
  2. 2021On Cross-Lingual Retrieval with Multilingual Text Encoderscited by 22
  3. 2022Parameter-Efficient Neural Reranking for Cross-Lingual and Multilingual Retrievalcited by 17
  4. 2021Evaluating Multilingual Text Encoders for Unsupervised Cross-Lingual Retrievalcited by 16
  5. 2021Learning Cross-Lingual IR from an English Retrievercited by 16
  6. 2022C3: Continued Pretraining with Contrastive Weak Supervision for Cross Language Ad-Hoc Retrievalcited by 14
  7. 2022CONCRETE: Improving Cross-lingual Fact-checking with Cross-lingual Retrievalcited by 14
  8. 2021X-METRA-ADA: Cross-lingual Meta-Transfer Learning Adaptation to Natural Language Understanding and Question Answeringcited by 10
  9. 2021Graph-based Multilingual Product Retrieval in E-commerce Searchcited by 9
  10. 2021Mixed Attention Transformer for Leveraging Word-Level Knowledge to Neural Cross-Lingual Information Retrievalcited by 8
  11. 2021Mind the Gap: Cross-Lingual Information Retrieval with Hierarchical Knowledge Enhancementcited by 8
  12. 2024Generative Retrieval as Multi-Vector Dense Retrievalcited by 8
15 more
  1. 2021Cross-Lingual Training with Dense Retrieval for Document Retrievalcited by 4
  2. 2023Machine Translation Impact in E-commerce Multilingual Searchcited by 4
  3. 2023Boosting Zero-shot Cross-lingual Retrieval by Training on Artificially Code-Switched Datacited by 4
  4. 2023Unified Embedding Based Personalized Retrieval in Etsy Searchcited by 4
  5. 2023Hubness Reduction Improves Sentence-BERT Semantic Spacescited by 4
  6. 2023ZC3: Zero-Shot Cross-Language Code Clone Detectioncited by 3
  7. 2024Unsupervised Multilingual Dense Retrieval via Generative Pseudo Labelingcited by 3
  8. 2025CLIRudit: Cross-Lingual Information Retrieval of Scientific Documentscited by 2
  9. 2025Anveshana: A New Benchmark Dataset for Cross-Lingual Information Retrieval On English Queries and Sanskrit Documentscited by 2
  10. 2021Leveraging Advantages of Interactive and Non-Interactive Models for Vector-Based Cross-Lingual Information Retrievalcited by 1
  11. 2021CDA: a Cost Efficient Content-based Multilingual Web Document Alignercited by 0
  12. 2021Cross-language Information Retrievalcited by 0
  13. 2024Enhancing E-commerce Product Title Translation with Retrieval-Augmented Generation and Large Language Modelscited by 0
  14. 2025Exploring new Approaches for Information Retrieval through Natural Language Processingcited by 0
  15. 2026Enhancing Generative Information Extraction with Two-step Validation: A Product Attribute Use Casecited by 0