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# Who cites «Effective Self-Training for Parsing»

252 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/aclbulk-2006-mcclosky-effective-self-training-parsing/)

Pages: **1** · [2](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/aclbulk-2006-mcclosky-effective-self-training-parsing-2/) · [3](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/aclbulk-2006-mcclosky-effective-self-training-parsing-3/)

1. [Creating a High Quality Abstract Meaning Representation Dataset Automatically](https://aclanthology.org/2026.lrec-1.932/) *— 2026 · Proceedings of the Fifteenth Language Resources and Evaluation Conference*
2. [Discovering and Causally Validating Emotion-Sensitive Neurons in Large Audio-Language Models](https://aclanthology.org/2026.acl-long.687/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
3. [DreamSync: Aligning Text-to-Image Generation with Image Understanding Feedback](https://aclanthology.org/2025.naacl-long.304/) *— 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)*
4. [Multistage Collaborative Knowledge Distillation from a Large Language Model for Semi-Supervised Sequence Generation](https://aclanthology.org/2024.acl-long.766/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
5. [Learning from a Friend: Improving Event Extraction via Self-Training with Feedback from Abstract Meaning Representation](https://aclanthology.org/2023.findings-acl.662/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
6. [Rethinking Semi-supervised Learning with Language Models](https://aclanthology.org/2023.findings-acl.347/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
7. [SCENE: Self-Labeled Counterfactuals for Extrapolating to Negative Examples](https://aclanthology.org/2023.emnlp-main.485/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
8. [Toolformer: Language Models Can Teach Themselves to Use Tools](https://arxiv.org/abs/2302.04761) *— 2023 · arXiv:2302.04761*
9. [A Comparison of Strategies for Source-Free Domain Adaptation](https://aclanthology.org/2022.acl-long.572/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
10. [A Few-Shot Semantic Parser for Wizard-of-Oz Dialogues with the Precise ThingTalk Representation](https://aclanthology.org/2022.findings-acl.317/) *— 2022 · Findings of the Association for Computational Linguistics: ACL 2022*
11. [Adapting to the Long Tail: A Meta-Analysis of Transfer Learning Research for Language Understanding Tasks](https://aclanthology.org/2022.tacl-1.56/) *— 2022 · Transactions of the Association for Computational Linguistics*
12. [Automatic Rule Induction for Efficient Semi-Supervised Learning](https://aclanthology.org/2022.findings-emnlp.3/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
13. [Co-training an Unsupervised Constituency Parser with Weak Supervision](https://aclanthology.org/2022.findings-acl.101/) *— 2022 · Findings of the Association for Computational Linguistics: ACL 2022*
14. [Improving Code-Switching Dependency Parsing with Semi-Supervised Auxiliary Tasks](https://aclanthology.org/2022.findings-naacl.87/) *— 2022 · Findings of the Association for Computational Linguistics: NAACL 2022*
15. [Neural Generation Meets Real People: Building a Social, Informative Open-Domain Dialogue Agent](https://aclanthology.org/2022.sigdial-1.37/) *— 2022 · Proceedings of the 23rd Annual Meeting of the Special Interest Group on Discourse and Dialogue*
16. [Out-of-Domain Discourse Dependency Parsing via Bootstrapping: An Empirical Analysis on Its Effectiveness and Limitation](https://aclanthology.org/2022.tacl-1.8/) *— 2022 · Transactions of the Association for Computational Linguistics*
17. [STAD: Self-Training with Ambiguous Data for Low-Resource Relation Extraction](https://aclanthology.org/2022.coling-1.178/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
18. [SynGEC: Syntax-Enhanced Grammatical Error Correction with a Tailored GEC-Oriented Parser](https://aclanthology.org/2022.emnlp-main.162/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
19. [Thematic Fit Bits: Annotation Quality and Quantity Interplay for Event Participant Representation](https://aclanthology.org/2022.lrec-1.556/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
20. [Break-It-Fix-It: Unsupervised Learning for Program Repair](https://arxiv.org/abs/2106.06600) *— 2021 · arXiv:2106.06600*
21. [Capturing document context inside sentence-level neural machine translation models with self-training](https://aclanthology.org/2021.codi-main.14/) *— 2021 · Proceedings of the 2nd Workshop on Computational Approaches to Discourse*
22. [Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond](https://arxiv.org/abs/2109.00725) *— 2021 · arXiv:2109.00725*
23. [Exploiting Cloze-Questions for Few-Shot Text Classification and Natural Language Inference](https://aclanthology.org/2021.eacl-main.20/) *— 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume*
24. [Improving Neural RST Parsing Model with Silver Agreement Subtrees](https://aclanthology.org/2021.naacl-main.127/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
25. [It''s Not Just Size That Matters: Small Language Models Are Also Few-Shot Learners](https://aclanthology.org/2021.naacl-main.185/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
26. [Multi-View Cross-Lingual Structured Prediction with Minimum Supervision](https://aclanthology.org/2021.acl-long.207/) *— 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)*
27. [Revisiting Self-training for Few-shot Learning of Language Model](https://aclanthology.org/2021.emnlp-main.718/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
28. [Revisiting Tri-training of Dependency Parsers](https://aclanthology.org/2021.emnlp-main.745/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
29. [STraTA: Self-Training with Task Augmentation for Better Few-shot Learning](https://aclanthology.org/2021.emnlp-main.462/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
30. [Self-Training for Compositional Neural NLG in Task-Oriented Dialogue](https://aclanthology.org/2021.inlg-1.10/) *— 2021 · Proceedings of the 14th International Conference on Natural Language Generation*
31. [Self-Training for Unsupervised Neural Machine Translation in Unbalanced Training Data Scenarios](https://aclanthology.org/2021.naacl-main.311/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
32. [Self-training Improves Pre-training for Natural Language Understanding](https://aclanthology.org/2021.naacl-main.426/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
33. [A Semi-supervised Approach for De-identification of Swedish Clinical Text](https://aclanthology.org/2020.lrec-1.547/) *— 2020 · Proceedings of the Twelfth Language Resources and Evaluation Conference*
34. [Affective Event Classification with Discourse-enhanced Self-training](https://aclanthology.org/2020.emnlp-main.452/) *— 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)*
35. [An Imitation Game for Learning Semantic Parsers from User Interaction](https://aclanthology.org/2020.emnlp-main.559/) *— 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)*
36. [AutoQA: From Databases To QA Semantic Parsers With Only Synthetic Training Data](https://aclanthology.org/2020.emnlp-main.31/) *— 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)*
37. [Combining Self-Training and Self-Supervised Learning for Unsupervised Disfluency Detection](https://aclanthology.org/2020.emnlp-main.142/) *— 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)*
38. [Cross-Lingual Dependency Parsing via Self-Training](https://aclanthology.org/2020.ccl-1.75/) *— 2020 · Proceedings of the 19th Chinese National Conference on Computational Linguistics*
39. [Data Augmentation via Subtree Swapping for Dependency Parsing of Low-Resource Languages](https://aclanthology.org/2020.coling-main.339/) *— 2020 · Proceedings of the 28th International Conference on Computational Linguistics*
40. [Detecting Urgency Status of Crisis Tweets: A Transfer Learning Approach for Low Resource Languages](https://aclanthology.org/2020.coling-main.414/) *— 2020 · Proceedings of the 28th International Conference on Computational Linguistics*
41. [Improving Disfluency Detection by Self-Training a Self-Attentive Model](https://aclanthology.org/2020.acl-main.346/) *— 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics*
42. [Leveraging User Paraphrasing Behavior In Dialog Systems To Automatically Collect Annotations For Long-Tail Utterances](https://aclanthology.org/2020.coling-industry.3/) *— 2020 · Proceedings of the 28th International Conference on Computational Linguistics: Industry Track*
43. [On the Role of Supervision in Unsupervised Constituency Parsing](https://aclanthology.org/2020.emnlp-main.614/) *— 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)*
44. [Self-Training for Unsupervised Parsing with PRPN](https://aclanthology.org/2020.iwpt-1.11/) *— 2020 · Proceedings of the 16th International Conference on Parsing Technologies and the IWPT 2020 Shared Task on Parsing into Enhanced Universal Dependencies*
45. [Semi-supervised Domain Adaptation for Dependency Parsing via Improved Contextualized Word Representations](https://aclanthology.org/2020.coling-main.338/) *— 2020 · Proceedings of the 28th International Conference on Computational Linguistics*
46. [SeqVAT: Virtual Adversarial Training for Semi-Supervised Sequence Labeling](https://aclanthology.org/2020.acl-main.777/) *— 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics*
47. [To BERT or Not to BERT: Comparing Task-specific and Task-agnostic Semi-Supervised Approaches for Sequence Tagging](https://aclanthology.org/2020.emnlp-main.636/) *— 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)*
48. [Unsupervised Discourse Constituency Parsing Using Viterbi EM](https://aclanthology.org/2020.tacl-1.15/) *— 2020 · Transactions of the Association for Computational Linguistics*
49. [Zero-shot Text Classification via Reinforced Self-training](https://aclanthology.org/2020.acl-main.272/) *— 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics*
50. [A Robust Self-Learning Framework for Cross-Lingual Text Classification](https://aclanthology.org/D19-1658/) *— 2019 · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)*
51. [Adversarial Learning with Contextual Embeddings for Zero-resource Cross-lingual Classification and NER](https://aclanthology.org/D19-1138/) *— 2019 · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)*
52. [Cross-lingual Annotation Projection Is Effective for Neural Part-of-Speech Tagging](https://aclanthology.org/W19-1425/) *— 2019 · Proceedings of the Sixth Workshop on NLP for Similar Languages, Varieties and Dialects*
53. [Leveraging Just a Few Keywords for Fine-Grained Aspect Detection Through Weakly Supervised Co-Training](https://aclanthology.org/D19-1468/) *— 2019 · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)*
54. [Neural Dependency Parsing of Biomedical Text: TurkuNLP entry in the CRAFT Structural Annotation Task](https://aclanthology.org/D19-5728/) *— 2019 · Proceedings of the 5th Workshop on BioNLP Open Shared Tasks*
55. [Neural Semantic Parsing in Low-Resource Settings with Back-Translation and Meta-Learning](https://arxiv.org/abs/1909.05438) *— 2019 · arXiv:1909.05438*
56. [Paraphrase Generation for Semi-Supervised Learning in NLU](https://aclanthology.org/W19-2306/) *— 2019 · Proceedings of the Workshop on Methods for Optimizing and Evaluating Neural Language Generation*
57. [To Annotate or Not? Predicting Performance Drop under Domain Shift](https://aclanthology.org/D19-1222/) *— 2019 · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)*
58. [Variational Pretraining for Semi-supervised Text Classification](https://aclanthology.org/P19-1590/) *— 2019 · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics*
59. [Extending a Parser to Distant Domains Using a Few Dozen Partially Annotated Examples](https://md.mova.elamur.ai/free/en/docs/papers/acl-2018-joshi-extending-parser-distant-domains-few/) *— our card · 2018 · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
60. [Human Needs Categorization of Affective Events Using Labeled and Unlabeled Data](https://aclanthology.org/N18-1174/) *— 2018 · Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)*
61. [Improving the results of string kernels in sentiment analysis and Arabic dialect identification by adapting them to your test set](https://aclanthology.org/D18-1135/) *— 2018 · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing*
62. [Semi-Supervised Sequence Modeling with Cross-View Training](https://aclanthology.org/D18-1217/) *— 2018 · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing*
63. [Speaker-Follower Models for Vision-and-Language Navigation](https://arxiv.org/abs/1806.02724) *— 2018 · arXiv:1806.02724*
64. [Strong Baselines for Neural Semi-Supervised Learning under Domain Shift](https://aclanthology.org/P18-1096/) *— 2018 · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
65. [Wronging a Right: Generating Better Errors to Improve Grammatical Error Detection](https://aclanthology.org/D18-1541/) *— 2018 · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing*
66. [Attention Is All You Need](https://arxiv.org/abs/1706.03762) *— 2017 · arXiv:1706.03762*
67. [Semi-supervised Structured Prediction with Neural CRF Autoencoder](https://aclanthology.org/D17-1179/) *— 2017 · Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing*
68. [Shift-Reduce Constituent Parsing with Neural Lookahead Features](https://aclanthology.org/Q17-1004/) *— 2017 · Transactions of the Association for Computational Linguistics*
69. [Transferring Semantic Roles Using Translation and Syntactic Information](https://aclanthology.org/I17-2003/) *— 2017 · Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers)*
70. [Unsupervised Domain Adaptation for Clinical Negation Detection](https://aclanthology.org/W17-2320/) *— 2017 · Proceedings of the 16th BioNLP Workshop*
71. [Word-Context Character Embeddings for Chinese Word Segmentation](https://aclanthology.org/D17-1079/) *— 2017 · Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing*
72. [Embedding Lexical Features via Low-Rank Tensors](https://aclanthology.org/N16-1117/) *— 2016 · Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
73. [From Noisy Questions to Minecraft Texts: Annotation Challenges in Extreme Syntax Scenario](https://aclanthology.org/W16-3905/) *— 2016 · Proceedings of the 2nd Workshop on Noisy User-generated Text (WNUT)*
74. [ICL-HD at SemEval-2016 Task 8: Meaning Representation Parsing - Augmenting AMR Parsing with a Preposition Semantic Role Labeling Neural Network](https://aclanthology.org/S16-1179/) *— 2016 · Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)*
75. [Improving Neural Machine Translation Models with Monolingual Data](https://aclanthology.org/P16-1009/) *— 2016 · Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
76. [Parsing as Language Modeling](https://aclanthology.org/D16-1257/) *— 2016 · Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing*
77. [Unsupervised Resolution of Acronyms and Abbreviations in Nursing Notes Using Document-Level Context Models](https://aclanthology.org/W16-6107/) *— 2016 · Proceedings of the Seventh International Workshop on Health Text Mining and Information Analysis*
78. [An Improved Tag Dictionary for Faster Part-of-Speech Tagging](https://aclanthology.org/D15-1151/) *— 2015 · Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing*
79. [Domain Adaptation for Dependency Parsing via Self-Training](https://aclanthology.org/W15-2201/) *— 2015 · Proceedings of the 14th International Conference on Parsing Technologies*
80. [Feature Optimization for Constituent Parsing via Neural Networks](https://aclanthology.org/P15-1110/) *— 2015 · Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
81. [Hubness and Pollution: Delving into Cross-Space Mapping for Zero-Shot Learning](https://aclanthology.org/P15-1027/) *— 2015 · Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
82. [Modeling Reportable Events as Turning Points in Narrative](https://aclanthology.org/D15-1257/) *— 2015 · Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing*
83. [Modelling and Optimizing on Syntactic N-Grams for Statistical Machine Translation](https://aclanthology.org/Q15-1013/) *— 2015 · Transactions of the Association for Computational Linguistics*
84. [Multi-domain Dialog State Tracking using Recurrent Neural Networks](https://aclanthology.org/P15-2130/) *— 2015 · Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)*
85. [Neural Reranking Improves Subjective Quality of Machine Translation: NAIST at WAT2015](https://aclanthology.org/W15-5003/) *— 2015 · Proceedings of the 2nd Workshop on Asian Translation (WAT2015)*
86. [Parsing Learner Text: to Shoehorn or not to Shoehorn](https://aclanthology.org/W15-1616/) *— 2015 · Proceedings of the 9th Linguistic Annotation Workshop*
87. [Parsing Paraphrases with Joint Inference](https://aclanthology.org/P15-1118/) *— 2015 · Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
88. [Semi-supervised Dependency Parsing using Bilexical Contextual Features from Auto-Parsed Data](https://aclanthology.org/D15-1158/) *— 2015 · Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing*
89. [Statistical Parsing by Machine Learning from a Classical Arabic Treebank](https://md.mova.elamur.ai/free/en/docs/papers/langstream-2015-dukes-statistical-parsing-machine-learning-classical/) *— our card · 2015 · arXiv:1510.07193*
90. [Structured Training for Neural Network Transition-Based Parsing](https://aclanthology.org/P15-1032/) *— 2015 · Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
91. [Transition-based Spinal Parsing](https://aclanthology.org/K15-1029/) *— 2015 · Proceedings of the Nineteenth Conference on Computational Natural Language Learning*
92. [Unsupervised Dependency Parsing: Let''s Use Supervised Parsers](https://aclanthology.org/N15-1067/) *— 2015 · Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
93. [A Domain-Restricted, Rule Based, English-Hindi Machine Translation System Based on Dependency Parsing](https://aclanthology.org/W14-5128/) *— 2014 · Proceedings of the 11th International Conference on Natural Language Processing*
94. [Adapting taggers to Twitter with not-so-distant supervision](https://aclanthology.org/C14-1168/) *— 2014 · Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers*
95. [Ambiguity-aware Ensemble Training for Semi-supervised Dependency Parsing](https://aclanthology.org/P14-1043/) *— 2014 · Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
96. [An Empirical Comparison of Parsing Methods for Stanford Dependencies](https://md.mova.elamur.ai/free/en/docs/papers/enud-2014-kong-empirical-comparison-parsing-methods-stanford/) *— our card · 2014 · arXiv:1404.4314*
97. [Automatic Corpus Expansion for Chinese Word Segmentation by Exploiting the Redundancy of Web Information](https://aclanthology.org/C14-1109/) *— 2014 · Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers*
98. [Cross-lingual Projected Expectation Regularization for Weakly Supervised Learning](https://aclanthology.org/Q14-1005/) *— 2014 · Transactions of the Association for Computational Linguistics*
99. [Exploring Compositional Architectures and Word Vector Representations for Prepositional Phrase Attachment](https://md.mova.elamur.ai/free/en/docs/papers/tacl-2014-belinkov-exploring-compositional-architectures-word-vector/) *— our card · 2014 · Transactions of the Association for Computational Linguistics*
100. [Generalizing a Strongly Lexicalized Parser using Unlabeled Data](https://aclanthology.org/E14-1014/) *— 2014 · Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics*

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