[Mova](https://md.mova.elamur.ai/free/en/) · [this page in HTML](https://mova.elamur.ai/free/en/docs/papers/cited-by/aclbulk-2006-mcclosky-effective-self-training-parsing-3/)

[home](https://md.mova.elamur.ai/free/en/) / [docs](https://md.mova.elamur.ai/free/en/docs/) / [papers](https://md.mova.elamur.ai/free/en/docs/papers/) / [cited-by](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/) / Who cites «Effective Self-Training for Parsing» · page 3

# Who cites «Effective Self-Training for Parsing» · page 3

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

1. [Unsupervised syntax-based machine translation: the contribution of discontiguous phrases](https://aclanthology.org/2007.mtsummit-papers.8/) *— 2007 · Proceedings of Machine Translation Summit XI: Papers*
2. [Using Self-Trained Bilexical Preferences to Improve Disambiguation Accuracy](https://aclanthology.org/W07-2201/) *— 2007 · Proceedings of the Tenth International Conference on Parsing Technologies*
3. [Weakly Supervised Learning for Hedge Classification in Scientific Literature](https://aclanthology.org/P07-1125/) *— 2007 · Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics*
4. [An All-Subtrees Approach to Unsupervised Parsing](https://aclanthology.org/P06-1109/) *— 2006 · Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics*
5. [Reranking and Self-Training for Parser Adaptation](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2006-mcclosky-reranking-self-training-parser-adaptation/) *— our card · 2006 · Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics*
6. agrawal-2017-three-phase-training-address-data
7. ahmadnia-2019-bilingual-low-resource-neural-machine
8. bergsma-2010-improved-natural-language-learning-variance
9. billingsley-2012-improvements-training-rnn-parser
10. celebi-2014-self-training-constituency-parser-n
11. cheung-2010-utilizing-extra-sentential-context-parsing
12. choe-2015-syntactic-parse-fusion
13. dridan-2010-unsupervised-parse-selection-hpsg
14. evang-2022-improving-low-resource-rrg-parsing
15. guo-2025-contrastive-learning-llm-back-generation
16. gupta-2021-multilingual-multilabel-emotion-recognition-virtual
17. gutierrez-2024-leveraging-structure-pre-trained-embeddings
18. hale-2019-text-genre-training-data-size
19. hogan-2008-parser-based-retraining-domain-adaptation
20. iii-2006-learning-phrasal-categories
21. jain-2013-effective-parsing-human-aided-nlp
22. kiso-2011-hits-based-seed-selection-stop
23. knaebel-2020-semi-supervised-tri-training-explicit
24. kummerfeld-2009-faster-parsing-supertagging-model-estimation
25. kurniawan-2022-unsupervised-cross-lingual-transfer-structured
26. le-2023-reducing-cohort-bias-natural-language
27. li-2022-semi-supervised-domain-adaptation-dependency
28. mackinlay-2013-extracting-biomedical-events-modifications-subgraph
29. mitchell-2016-decomposing-bilexical-dependencies-into-semantic
30. ovchinnikova-2013-abduction-discourse-interpretation-probabilistic-framework
31. park-2018-le-benchmarking-de-la-reconnaissance
32. ronen-2022-multi-domain-targeted-sentiment-analysis
33. rudinger-2017-skip-prop-representing-sentences-one
34. saez-2009-statistical-confidence-measures-probabilistic-parsing
35. saez-2010-confidence-measures-error-discrimination-interactive
36. sarafraz-2010-svms-command-relation-features-identify
37. seddah-2012-ubiquitous-usage-broad-coverage-french
38. shi-2024-structured-tree-alignment-evaluation-speech
39. shivade-2016-addressing-limited-data-textual-entailment
40. tamang-2012-relabeling-distantly-supervised-training-data
41. teranishi-2022-coordination-generation-synchronized-text-infilling
42. visweswariah-2013-cut-noise-mutually-reinforcing-reordering
43. wang-2012-effort-genre-variation-prediction-system
44. wang-2020-semi-supervised-dependency-parsing-arc
45. yang-2009-generalizable-features-help-semantic-role
46. yin-2024-source-free-domain-adaptation-question
47. yu-2015-exploring-confidence-based-self-training
48. zhang-2023-data-efficient-active-learning-structured
49. zhang-2023-friend-training-learning-models-different
50. zhou-2016-evaluating-deterministic-shift-reduce-neural
51. zhu-2021-combining-deep-generative-models-multi
52. zhu-2022-unsupervised-domain-adaptation-question-generation

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

- [← previous Who cites «Effective Self-Training for Parsing» · page 2](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/aclbulk-2006-mcclosky-effective-self-training-parsing-2/)
- [next → Who cites «Reranking and Self-Training for Parser Adaptation»](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/aclbulk-2006-mcclosky-reranking-self-training-parser-adaptation/)
- [↑ back to papers/cited-by/](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/)