mlsanityData to 14 Oct 2026

Curriculum Learning for Domain Adaptation in Neural Machine Translation

arXiv 1905.05816 ↗First posted 14 May 2019cs.CLcited by 59

Not on the map. Why?

Abstract (arXiv)

We introduce a curriculum learning approach to adapt generic neural machine translation models to a specific domain. Samples are grouped by their similarities to the domain of interest and each group is fed to the training algorithm with a particular schedule. This approach is simple to implement on top of any neural framework or architecture, and consistently outperforms both unadapted and adapted baselines in experiments with two distinct domains and two language pairs.

Key facts. Cited by 59 papers in the map (data through 14 Oct 2026). First posted on arXiv 14 May 2019.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 21; 2022: 10; 2023: 15; 2024: 6; 2025: 2; 2026: 5.

59 papers.

Sort:

By area:

  1. 2021Curriculum Learning: A Surveycited by 259
  2. 2022Efficient Methods for Natural Language Processing: A Surveycited by 78
  3. 2021Domain Adaptation and Multi-Domain Adaptation for Neural Machine Translation: A Surveycited by 46
  4. 2024Curry-DPO: Enhancing Alignment using Curriculum Learning & Ranked Preferencescited by 39
  5. 2021The Stability-Efficiency Dilemma: Investigating Sequence Length Warmup for Training GPT Modelscited by 36
  6. 2021Does the Order of Training Samples Matter? Improving Neural Data-to-Text Generation with Curriculum Learningcited by 34
  7. 2021Prevent the Language Model from being Overconfident in Neural Machine Translationcited by 34
  8. 2021NLP From Scratch Without Large-Scale Pretraining: A Simple and Efficient Frameworkcited by 34
  9. 2021Curriculum learning for language modelingcited by 32
  10. 2021Meta-Curriculum Learning for Domain Adaptation in Neural Machine Translationcited by 28
  11. 2021An Analytical Theory of Curriculum Learning in Teacher-Student Networkscited by 27
  12. 2023CiT: Curation in Training for Effective Vision-Language Datacited by 27
38 more
  1. 2021Progressive Multi-Granularity Training for Non-Autoregressive Translationcited by 25
  2. 2021Gradual Fine-Tuning for Low-Resource Domain Adaptationcited by 24
  3. 2021Gradual Domain Adaptation in the Wild:When Intermediate Distributions are Absentcited by 21
  4. 2021Pruning-then-Expanding Model for Domain Adaptation of Neural Machine Translationcited by 15
  5. 2022DeepSpeed Data Efficiency: Improving Deep Learning Model Quality and Training Efficiency via Efficient Data Sampling and Routingcited by 13
  6. 2023Curricular Object Manipulation in LiDAR-based Object Detectioncited by 12
  7. 2021Improving Both Domain Robustness and Domain Adaptability in Machine Translationcited by 11
  8. 2021Towards User-Driven Neural Machine Translationcited by 10
  9. 2021Self-Guided Curriculum Learning for Neural Machine Translationcited by 9
  10. 2022When Do Curricula Work in Federated Learning?cited by 9
  11. 2021NVIDIA NeMo Neural Machine Translation Systems for English-German and English-Russian News and Biomedical Tasks at WMT21cited by 8
  12. 2024To Label or Not to Label: Hybrid Active Learning for Neural Machine Translationcited by 8
  13. 2023Curriculum-Based Augmented Fourier Domain Adaptation for Robust Medical Image Segmentationcited by 7
  14. 2021Exploiting Curriculum Learning in Unsupervised Neural Machine Translationcited by 6
  15. 2023Digital Twin-based Anomaly Detection with Curriculum Learning in Cyber-physical Systemscited by 6
  16. 2023Error Norm Truncation: Robust Training in the Presence of Data Noise for Text Generation Modelscited by 6
  17. 2022Training Dynamics for Curriculum Learning: A Study on Monolingual and Cross-lingual NLUcited by 5
  18. 2023Mitigating Data Imbalance and Representation Degeneration in Multilingual Machine Translationcited by 5
  19. 2021Token-wise Curriculum Learning for Neural Machine Translationcited by 4
  20. 2022Cyclical Curriculum Learningcited by 4
  21. 2022In-sample Curriculum Learning by Sequence Completion for Natural Language Generationcited by 4
  22. 2022CLID: Controlled-Length Image Descriptions with Limited Datacited by 4
  23. 2024Choose the Final Translation from NMT and LLM hypotheses Using MBR Decoding: HW-TSC's Submission to the WMT24 General MT Shared Taskcited by 4
  24. 2023Ling-CL: Understanding NLP Models through Linguistic Curriculacited by 3
  25. 2023Complexity-Guided Curriculum Learning for Text Graphscited by 3
  26. 2025Teaching with Lies: Curriculum DPO on Synthetic Negatives for Hallucination Detectioncited by 3
  27. 2023Curriculum Learning for Graph Neural Networks: A Multiview Competence-based Approachcited by 2
  28. 2023Curriculum Guided Domain Adaptation in the Darkcited by 2
  29. 2023Harnessing Dataset Cartography for Improved Compositional Generalization in Transformerscited by 2
  30. 2021Statistical Measures For Defining Curriculum Scoring Functioncited by 1
  31. 2021Learning Policies for Multilingual Training of Neural Machine Translation Systemscited by 1
  32. 2022Progressive Sentiment Analysis for Code-Switched Text Datacited by 1
  33. 2022Confidence-Aware Paced-Curriculum Learning by Label Smoothing for Surgical Scene Understandingcited by 1
  34. 2023HuCurl: Human-induced Curriculum Discoverycited by 1
  35. 2023Simple and Effective Input Reformulations for Translationcited by 1
  36. 2024HW-TSC's Submission to the CCMT 2024 Machine Translation Taskscited by 1
  37. 2022Finding the Right Recipe for Low Resource Domain Adaptation in Neural Machine Translationcited by 0
  38. 2023Epi-Curriculum: Episodic Curriculum Learning for Low-Resource Domain Adaptation in Neural Machine Translationcited by 0

50 most cited of 59 All 59 (JSON)