mlsanityData to 7 Oct 2026

Adversarial Learning with Contextual Embeddings for Zero-resource Cross-lingual Classification and NER

arXiv 1909.00153 ↗First posted 31 Aug 2019cs.CL cs.LGcited by 25

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Abstract (arXiv)

Contextual word embeddings (e.g. GPT, BERT, ELMo, etc.) have demonstrated state-of-the-art performance on various NLP tasks. Recent work with the multilingual version of BERT has shown that the model performs very well in zero-shot and zero-resource cross-lingual settings, where only labeled English data is used to finetune the model. We improve upon multilingual BERT's zero-resource cross-lingual performance via adversarial learning. We report the magnitude of the improvement on the multilingual MLDoc text classification and CoNLL 2002/2003 named entity recognition tasks. Furthermore, we show that language-adversarial training encourages BERT to align the embeddings of English documents and their translations, which may be the cause of the observed performance gains.

Key facts. Cited by 25 papers in the map (data through 7 Oct 2026). First posted on arXiv 31 Aug 2019.

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Citing papers per year: 2021: 7; 2022: 7; 2023: 8; 2024: 3.

25 papers.

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  1. 2022Enhancing Cross-lingual Transfer by Manifold Mixupcited by 30
  2. 2022English Contrastive Learning Can Learn Universal Cross-lingual Sentence Embeddingscited by 26
  3. 2021AdvPicker: Effectively Leveraging Unlabeled Data via Adversarial Discriminator for Cross-Lingual NERcited by 17
  4. 2021Contributions of Transformer Attention Heads in Multi- and Cross-lingual Taskscited by 16
  5. 2021Everything Is All It Takes: A Multipronged Strategy for Zero-Shot Cross-Lingual Information Extractioncited by 16
  6. 2023mCL-NER: Cross-Lingual Named Entity Recognition via Multi-view Contrastive Learningcited by 14
  7. 2021Nearest Neighbour Few-Shot Learning for Cross-lingual Classificationcited by 8
  8. 2023A Survey on Arabic Named Entity Recognition: Past, Recent Advances, and Future Trendscited by 8
  9. 2023Improving Self-training for Cross-lingual Named Entity Recognition with Contrastive and Prototype Learningcited by 8
  10. 2022WIDER & CLOSER: Mixture of Short-channel Distillers for Zero-shot Cross-lingual Named Entity Recognitioncited by 7
  11. 2024Multilingual Sentence-T5: Scalable Sentence Encoders for Multilingual Applicationscited by 7
  12. 2022Few-Shot Cross-lingual Transfer for Coarse-grained De-identification of Code-Mixed Clinical Textscited by 5
13 more
  1. 2022Domain Adaptation in Multilingual and Multi-Domain Monolingual Settings for Complex Word Identificationcited by 3
  2. 2021A Multilingual Bag-of-Entities Model for Zero-Shot Cross-Lingual Text Classificationcited by 2
  3. 2022A Dual-Contrastive Framework for Low-Resource Cross-Lingual Named Entity Recognitioncited by 2
  4. 2022Cross-lingual Transfer Learning for Check-worthy Claim Identification over Twittercited by 2
  5. 2024CMNER: A Chinese Multimodal NER Dataset based on Social Mediacited by 2
  6. 2024Improving Pseudo Labels with Global-Local Denoising Framework for Cross-lingual Named Entity Recognitioncited by 2
  7. 2023SHINE: Syntax-augmented Hierarchical Interactive Encoder for Zero-shot Cross-lingual Information Extractioncited by 1
  8. 2023Out-of-Distribution Generalization in Text Classification: Past, Present, and Futurecited by 1
  9. 2023CoLaDa: A Collaborative Label Denoising Framework for Cross-lingual Named Entity Recognitioncited by 1
  10. 2021Zero-Resource Multi-Dialectal Arabic Natural Language Understandingcited by 0
  11. 2021Zero-Shot Cross-Lingual Transfer in Legal Domain Using Transformer Modelscited by 0
  12. 2023Learning for Amalgamation: A Multi-Source Transfer Learning Framework For Sentiment Classificationcited by 0
  13. 2023Sharing, Teaching and Aligning: Knowledgeable Transfer Learning for Cross-Lingual Machine Reading Comprehensioncited by 0