---
title: "Who cites Improving Arabic Diacritization with Regularized…"
description: "The papers of the Elamur Research library that cite «Improving Arabic Diacritization with Regularized Decoding and Adversarial Training», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/acl-2021-qin-improving-arabic-diacritization-regularized-decoding/cited-by/"
---
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# Who cites «Improving Arabic Diacritization with Regularized Decoding and Adversarial Training»

15 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. [← the card](https://md.research.elamur.ai/free/en/papers/acl-2021-qin-improving-arabic-diacritization-regularized-decoding/)

1. [Eraserhead at OSACT7 Shared Task: ASR Consistency Filtering and Speaker-Adaptive Post-Processing for Arabic Speech Diacritization](https://aclanthology.org/2026.osact-1.32/) *— 2026 · The 7th Workshop on Open-Source Arabic Corpora and Processing Tools (OSACT7) with 5 Shared Tasks*
2. [Arabic Diacritics in the Wild: Exploiting Opportunities for Improved Diacritization](https://aclanthology.org/2024.acl-long.792/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
3. [Arabic Text Diacritization In The Age Of Transfer Learning: Token Classification Is All You Need](https://arxiv.org/abs/2401.04848) *— 2024 · arXiv:2401.04848*
4. [Interplay of Machine Translation, Diacritics, and Diacritization](https://aclanthology.org/2024.naacl-long.420/) *— 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)*
5. [Take the Hint: Improving Arabic Diacritization with Partially-Diacritized Text](https://arxiv.org/abs/2306.03557) *— 2023 · arXiv:2306.03557*
6. [ChiMST: A Chinese Medical Corpus for Word Segmentation and Medical Term Recognition](https://aclanthology.org/2022.lrec-1.607/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
7. [Complementary Learning of Aspect Terms for Aspect-based Sentiment Analysis](https://aclanthology.org/2022.lrec-1.760/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
8. [Enhancing Relation Extraction via Adversarial Multi-task Learning](https://aclanthology.org/2022.lrec-1.666/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
9. [Enhancing Structure-aware Encoder with Extremely Limited Data for Graph-based Dependency Parsing](https://aclanthology.org/2022.coling-1.483/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
10. [Improving English-Arabic Transliteration with Phonemic Memories](https://aclanthology.org/2022.findings-emnlp.238/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
11. [Improving Relation Extraction through Syntax-induced Pre-training with Dependency Masking](https://aclanthology.org/2022.findings-acl.147/) *— 2022 · Findings of the Association for Computational Linguistics: ACL 2022*
12. [Dependency-driven Relation Extraction with Attentive Graph Convolutional Networks](https://aclanthology.org/2021.acl-long.344/) *— 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)*
13. [Federated Chinese Word Segmentation with Global Character Associations](https://aclanthology.org/2021.findings-acl.376/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
14. [Improving Federated Learning for Aspect-based Sentiment Analysis via Topic Memories](https://aclanthology.org/2021.emnlp-main.321/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*
15. [Relation Extraction with Word Graphs from N-grams](https://aclanthology.org/2021.emnlp-main.228/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*