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# Who cites «Curriculum Learning» · page 3

659 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. [← the card](https://md.mova.elamur.ai/free/en/docs/papers/bengio-2009-curriculum-learning/)

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1. [WeCheck: Strong Factual Consistency Checker via Weakly Supervised Learning](https://aclanthology.org/2023.acl-long.18/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
2. [A Generalist Neural Algorithmic Learner](https://arxiv.org/abs/2209.11142) *— 2022 · arXiv:2209.11142*
3. [A Human-machine Interface for Few-shot Rule Synthesis for Information Extraction](https://aclanthology.org/2022.naacl-demo.8/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: System Demonstrations*
4. [A Model-agnostic Data Manipulation Method for Persona-based Dialogue Generation](https://aclanthology.org/2022.acl-long.550/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
5. [A Survey of Active Learning for Natural Language Processing](https://arxiv.org/abs/2210.10109) *— 2022 · arXiv:2210.10109*
6. [ALLSH: Active Learning Guided by Local Sensitivity and Hardness](https://aclanthology.org/2022.findings-naacl.99/) *— 2022 · Findings of the Association for Computational Linguistics: NAACL 2022*
7. [Active Learning on a Budget: Opposite Strategies Suit High and Low Budgets](https://arxiv.org/abs/2202.02794) *— 2022 · arXiv:2202.02794 · 39th International Conference on Machine Learning, Baltimore, Maryland, USA, PMLR 162, 2022*
8. [Adaptor: Objective-Centric Adaptation Framework for Language Models](https://aclanthology.org/2022.acl-demo.26/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations*
9. [Balancing Multi-Domain Corpora Learning for Open-Domain Response Generation](https://aclanthology.org/2022.findings-naacl.162/) *— 2022 · Findings of the Association for Computational Linguistics: NAACL 2022*
10. [Better Language Model with Hypernym Class Prediction](https://aclanthology.org/2022.acl-long.96/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
11. [Challenges of Neural Machine Translation for Short Texts](https://aclanthology.org/2022.cl-2.3/) *— 2022 · Computational Linguistics*
12. [Clean or Annotate: How to Spend a Limited Data Collection Budget](https://aclanthology.org/2022.deeplo-1.17/) *— 2022 · Proceedings of the Third Workshop on Deep Learning for Low-Resource Natural Language Processing*
13. [ClidSum: A Benchmark Dataset for Cross-Lingual Dialogue Summarization](https://aclanthology.org/2022.emnlp-main.526/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
14. [Cross-Modal Similarity-Based Curriculum Learning for Image Captioning](https://aclanthology.org/2022.emnlp-main.516/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
15. [Crossroads, Buildings and Neighborhoods: A Dataset for Fine-grained Location Recognition](https://aclanthology.org/2022.naacl-main.243/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
16. [Curriculum Prompt Learning with Self-Training for Abstractive Dialogue Summarization](https://aclanthology.org/2022.emnlp-main.72/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
17. [Curriculum-guided Abstractive Summarization for Mental Health Online Posts](https://aclanthology.org/2022.louhi-1.17/) *— 2022 · Proceedings of the 13th International Workshop on Health Text Mining and Information Analysis (LOUHI)*
18. [Data Selection Curriculum for Neural Machine Translation](https://aclanthology.org/2022.findings-emnlp.113/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
19. [Distilling Causal Effect from Miscellaneous Other-Class for Continual Named Entity Recognition](https://aclanthology.org/2022.emnlp-main.236/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
20. [Do Data-based Curricula Work?](https://aclanthology.org/2022.insights-1.16/) *— 2022 · Proceedings of the Third Workshop on Insights from Negative Results in NLP*
21. [Efficient Pre-training of Masked Language Model via Concept-based Curriculum Masking](https://aclanthology.org/2022.emnlp-main.502/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
22. [Extreme Zero-Shot Learning for Extreme Text Classification](https://aclanthology.org/2022.naacl-main.399/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
23. [Feeding What You Need by Understanding What You Learned](https://aclanthology.org/2022.acl-long.403/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
24. [From Examples to Rules: Neural Guided Rule Synthesis for Information Extraction](https://aclanthology.org/2022.lrec-1.665/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
25. [Generalizing Morphological Inflection Systems to Unseen Lemmas](https://aclanthology.org/2022.sigmorphon-1.23/) *— 2022 · Proceedings of the 19th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology*
26. [Generative Entity Typing with Curriculum Learning](https://aclanthology.org/2022.emnlp-main.199/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
27. [Generic and Trend-aware Curriculum Learning for Relation Extraction](https://aclanthology.org/2022.naacl-main.160/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
28. [Hierarchical Curriculum Learning for AMR Parsing](https://aclanthology.org/2022.acl-short.37/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*
29. [Improving Both Domain Robustness and Domain Adaptability in Machine Translation](https://aclanthology.org/2022.coling-1.461/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
30. [Interpretable Low-Resource Legal Decision Making](https://arxiv.org/abs/2201.01164) *— 2022 · arXiv:2201.01164*
31. [Isolated Sign Recognition using ASL Datasets with Consistent Text-based Gloss Labeling and Curriculum Learning](https://aclanthology.org/2022.sltat-1.3/) *— 2022 · Proceedings of the 7th International Workshop on Sign Language Translation and Avatar Technology: The Junction of the Visual and the Textual: Challenges and Perspectives*
32. [Learning to Perform Complex Tasks through Compositional Fine-Tuning of Language Models](https://aclanthology.org/2022.findings-emnlp.121/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
33. [Multi-Domain Adaptation in Neural Machine Translation with Dynamic Sampling Strategies](https://aclanthology.org/2022.eamt-1.4/) *— 2022 · Proceedings of the 23rd Annual Conference of the European Association for Machine Translation*
34. [No Language Left Behind: Scaling Human-Centered Machine Translation](https://arxiv.org/abs/2207.04672) *— 2022 · arXiv:2207.04672*
35. [On Curriculum Learning for Commonsense Reasoning](https://aclanthology.org/2022.naacl-main.72/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
36. [Parsing Natural Language into Propositional and First-Order Logic with Dual Reinforcement Learning](https://aclanthology.org/2022.coling-1.481/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
37. [Peano: Learning Formal Mathematical Reasoning](https://arxiv.org/abs/2211.15864) *— 2022 · arXiv:2211.15864*
38. [Predicting Difficulty and Discrimination of Natural Language Questions](https://aclanthology.org/2022.acl-short.15/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*
39. [Samanantar: The Largest Publicly Available Parallel Corpora Collection for 11 Indic Languages](https://aclanthology.org/2022.tacl-1.9/) *— 2022 · Transactions of the Association for Computational Linguistics*
40. [Semantic Similarity Based Filtering for Turkish Paraphrase Dataset Creation](https://aclanthology.org/2022.icnlsp-1.14/) *— 2022 · Proceedings of the 5th International Conference on Natural Language and Speech Processing (ICNLSP 2022)*
41. [Situated Dialogue Learning through Procedural Environment Generation](https://aclanthology.org/2022.acl-long.557/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
42. [Supervised Prototypical Contrastive Learning for Emotion Recognition in Conversation](https://aclanthology.org/2022.emnlp-main.347/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
43. [TAKE: Topic-shift Aware Knowledge sElection for Dialogue Generation](https://aclanthology.org/2022.coling-1.20/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
44. [The Grammar-Learning Trajectories of Neural Language Models](https://aclanthology.org/2022.acl-long.568/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
45. [Uncertainty Estimation and Reduction of Pre-trained Models for Text Regression](https://aclanthology.org/2022.tacl-1.39/) *— 2022 · Transactions of the Association for Computational Linguistics*
46. [UniDU: Towards A Unified Generative Dialogue Understanding Framework](https://aclanthology.org/2022.sigdial-1.43/) *— 2022 · Proceedings of the 23rd Annual Meeting of the Special Interest Group on Discourse and Dialogue*
47. [Unsupervised Domain Adaptation for Text Classification via Meta Self-Paced Learning](https://aclanthology.org/2022.coling-1.420/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
48. [Vision-and-Language Navigation: A Survey of Tasks, Methods, and Future Directions](https://aclanthology.org/2022.acl-long.524/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
49. [What Can Transformers Learn In-Context? A Case Study of Simple Function Classes](https://arxiv.org/abs/2208.01066) *— 2022 · arXiv:2208.01066*
50. [Active Curriculum Learning](https://aclanthology.org/2021.internlp-1.6/) *— 2021 · Proceedings of the First Workshop on Interactive Learning for Natural Language Processing*
51. [Advances in Machine and Deep Learning for Modeling and Real-time Detection of Multi-Messenger Sources](https://arxiv.org/abs/2105.06479) *— 2021 · arXiv:2105.06479*
52. [Bandits Don''t Follow Rules: Balancing Multi-Facet Machine Translation with Multi-Armed Bandits](https://aclanthology.org/2021.findings-emnlp.274/) *— 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021*
53. [Can Transformer Language Models Predict Psychometric Properties?](https://aclanthology.org/2021.starsem-1.2/) *— 2021 · Proceedings of *SEM 2021: The Tenth Joint Conference on Lexical and Computational Semantics*
54. [Combining Curriculum Learning and Knowledge Distillation for Dialogue Generation](https://aclanthology.org/2021.findings-emnlp.111/) *— 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021*
55. [Competence-based Curriculum Learning for Multilingual Machine Translation](https://aclanthology.org/2021.findings-emnlp.212/) *— 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021*
56. [Competence-based Multimodal Curriculum Learning for Medical Report Generation](https://aclanthology.org/2021.acl-long.234/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
57. [Critical Thinking for Language Models](https://aclanthology.org/2021.iwcs-1.7/) *— 2021 · Proceedings of the 14th International Conference on Computational Semantics (IWCS)*
58. [Data Augmentation for Text Generation Without Any Augmented Data](https://aclanthology.org/2021.acl-long.173/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
59. [Dialogue Response Selection with Hierarchical Curriculum Learning](https://aclanthology.org/2021.acl-long.137/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
60. [Diverse Distributions of Self-Supervised Tasks for Meta-Learning in NLP](https://aclanthology.org/2021.emnlp-main.469/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
61. [Does the Order of Training Samples Matter? Improving Neural Data-to-Text Generation with Curriculum Learning](https://aclanthology.org/2021.eacl-main.61/) *— 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume*
62. [Edit Distance Based Curriculum Learning for Paraphrase Generation](https://aclanthology.org/2021.acl-srw.24/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: Student Research Workshop*
63. [Exploiting Curriculum Learning in Unsupervised Neural Machine Translation](https://aclanthology.org/2021.findings-emnlp.79/) *— 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021*
64. [Fast Multi-Resolution Transformer Fine-tuning for Extreme Multi-label Text Classification](https://arxiv.org/abs/2110.00685) *— 2021 · arXiv:2110.00685*
65. [Fast-MD: Fast Multi-Decoder End-to-End Speech Translation with Non-Autoregressive Hidden Intermediates](https://arxiv.org/abs/2109.12804) *— 2021 · arXiv:2109.12804*
66. [Few-Shot Text Classification with Triplet Networks, Data Augmentation, and Curriculum Learning](https://aclanthology.org/2021.naacl-main.434/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
67. [Generalization in Text-based Games via Hierarchical Reinforcement Learning](https://aclanthology.org/2021.findings-emnlp.116/) *— 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021*
68. [Glancing Transformer for Non-Autoregressive Neural Machine Translation](https://aclanthology.org/2021.acl-long.155/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
69. [Gradual Fine-Tuning for Low-Resource Domain Adaptation](https://aclanthology.org/2021.adaptnlp-1.22/) *— 2021 · Proceedings of the Second Workshop on Domain Adaptation for NLP*
70. [Improving Distantly-Supervised Named Entity Recognition with Self-Collaborative Denoising Learning](https://aclanthology.org/2021.findings-emnlp.131/) *— 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021*
71. [Improving Low-Resource Named Entity Recognition via Label-Aware Data Augmentation and Curriculum Denoising](https://aclanthology.org/2021.ccl-1.101/) *— 2021 · Proceedings of the 20th Chinese National Conference on Computational Linguistics*
72. [Improving Sequence-to-Sequence Pre-training via Sequence Span Rewriting](https://aclanthology.org/2021.emnlp-main.45/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
73. [Increasing Robustness to Spurious Correlations using Forgettable Examples](https://aclanthology.org/2021.eacl-main.291/) *— 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume*
74. [Learning Algebraic Recombination for Compositional Generalization](https://aclanthology.org/2021.findings-acl.97/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
75. [Multi-stage Pre-training over Simplified Multimodal Pre-training Models](https://aclanthology.org/2021.acl-long.199/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
76. [NL-EDIT: Correcting Semantic Parse Errors through Natural Language Interaction](https://aclanthology.org/2021.naacl-main.444/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
77. [On the Role of Corpus Ordering in Language Modeling](https://aclanthology.org/2021.sustainlp-1.15/) *— 2021 · Proceedings of the Second Workshop on Simple and Efficient Natural Language Processing*
78. [On the limit of English conversational speech recognition](https://arxiv.org/abs/2105.00982) *— 2021 · arXiv:2105.00982*
79. [Open Hierarchical Relation Extraction](https://aclanthology.org/2021.naacl-main.452/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
80. [PLATO-2: Towards Building an Open-Domain Chatbot via Curriculum Learning](https://aclanthology.org/2021.findings-acl.222/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
81. [Pre-training a BERT with Curriculum Learning by Increasing Block-Size of Input Text](https://aclanthology.org/2021.ranlp-1.112/) *— 2021 · Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021)*
82. [Preview, Attend and Review: Schema-Aware Curriculum Learning for Multi-Domain Dialogue State Tracking](https://aclanthology.org/2021.acl-short.111/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)*
83. [Progressive Multi-Granularity Training for Non-Autoregressive Translation](https://aclanthology.org/2021.findings-acl.247/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
84. [Progressive Self-Training with Discriminator for Aspect Term Extraction](https://aclanthology.org/2021.emnlp-main.23/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
85. [Progressive Transformer-Based Generation of Radiology Reports](https://aclanthology.org/2021.findings-emnlp.241/) *— 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021*
86. [Progressively Pretrained Dense Corpus Index for Open-Domain Question Answering](https://aclanthology.org/2021.eacl-main.244/) *— 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume*
87. [Quantifying Appropriateness of Summarization Data for Curriculum Learning](https://aclanthology.org/2021.eacl-main.119/) *— 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume*
88. [Self-Guided Curriculum Learning for Neural Machine Translation](https://aclanthology.org/2021.iwslt-1.25/) *— 2021 · Proceedings of the 18th International Conference on Spoken Language Translation (IWSLT 2021)*
89. [Self-Supervised Curriculum Learning for Spelling Error Correction](https://aclanthology.org/2021.emnlp-main.281/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
90. [Shortformer: Better Language Modeling using Shorter Inputs](https://aclanthology.org/2021.acl-long.427/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
91. [Test Harder than You Train: Probing with Extrapolation Splits](https://aclanthology.org/2021.blackboxnlp-1.2/) *— 2021 · Proceedings of the Fourth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP*
92. [Text2Event: Controllable Sequence-to-Structure Generation for End-to-end Event Extraction](https://aclanthology.org/2021.acl-long.217/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
93. [The Stability-Efficiency Dilemma: Investigating Sequence Length Warmup for Training GPT Models](https://arxiv.org/abs/2108.06084) *— 2021 · arXiv:2108.06084*
94. [Trigger is Not Sufficient: Exploiting Frame-aware Knowledge for Implicit Event Argument Extraction](https://aclanthology.org/2021.acl-long.360/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
95. [Understanding Dataset Difficulty with $\mathcal{V}$-Usable Information](https://arxiv.org/abs/2110.08420) *— 2021 · arXiv:2110.08420*
96. [xMoCo: Cross Momentum Contrastive Learning for Open-Domain Question Answering](https://aclanthology.org/2021.acl-long.477/) *— 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
97. [A Survey on Curriculum Learning](https://arxiv.org/abs/2010.13166) *— 2020 · arXiv:2010.13166*
98. [Assessing the Bilingual Knowledge Learned by Neural Machine Translation Models](https://arxiv.org/abs/2004.13270) *— 2020 · arXiv:2004.13270*
99. [Automatic Curriculum Learning For Deep RL: A Short Survey](https://arxiv.org/abs/2003.04664) *— 2020 · arXiv:2003.04664*
100. [BERT-of-Theseus: Compressing BERT by Progressive Module Replacing](https://aclanthology.org/2020.emnlp-main.633/) *— 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)*

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