---
title: "Who cites Data Augmentation using Large — 26 citing papers"
description: "26 papers of the Elamur Research library cite «Data Augmentation using Large Language Models: Data Perspectives, Learning Paradigms…"
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---
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# Who cites «Data Augmentation using Large Language Models: Data Perspectives, Learning Paradigms and Challenges»

26 papers of our library cite it (of the 149,439 whose bibliographies we read) · 6 with a page here, the most cited first · [← back to «Data Augmentation using Large Language Models: Data Perspectives, Learning Paradigms and Challenges»](https://md.research.elamur.ai/free/en/papers/ding-2024-data-augmentation-using-large-language/)

1. [**Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models arXiv:2501.09686**Fengli Xu, Qianyue Hao, Zefang Zong, et al.*2025 · 120 citations*](https://md.research.elamur.ai/free/en/papers/xu-2025-towards-large-reasoning-models-survey/)
2. **[ActiveLLM: Large Language Model-Based Active Learning for Textual Few-Shot Scenarios](https://md.research.elamur.ai/free/en/papers/bayer-2026-activellm-large-language-model-based/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Markus Bayer, Justin Lutz, Christian Reuter*2026 · 16 citations*
3. **[EXCGEC: A Benchmark for Edit-Wise Explainable Chinese Grammatical Error Correction](https://md.research.elamur.ai/free/en/papers/ye-2024-excgec-benchmark-edit-wise-explainable/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Jingheng Ye, Shang Qin, Yinghui Li, et al.*2024 · 15 citations*
4. **[LLM-to-Speech: A Synthetic Data Pipeline for Training Dialectal Text-to-Speech Models](https://md.research.elamur.ai/free/en/papers/khamis-2026-llm-speech-synthetic-data-pipeline/) [Workshop on NLP for Languages Using Arabic Script](https://md.research.elamur.ai/free/en/venues/abjadnlp/)**Ahmed Khamis, Hesham Ali Ahmed*2026 · 1 citation*
5. **[Corruption-Based Data Augmentation for Arabic Essay Scoring: A Preliminary Study on the Organization Trait](https://md.research.elamur.ai/free/en/papers/bashendy-2026-corruption-based-data-augmentation-arabic/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**May Saed Bashendy, Tamer Elsayed*2026*
6. **[Memory-Guided Hard Data Augmentation for Multimodal Named Entity Recognition](https://md.research.elamur.ai/free/en/papers/liu-2026-memory-guided-hard-data-augmentation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xinyu Liu, Kai fu, Yinghan Shi, et al.*2026*

20 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/ding-2024-data-augmentation-using-large-language/) — Data Augmentation using Large Language Models: Data Perspectives, Learning Paradigms and Challenges