---
title: "makcedward/nlpaug: papers citing this GitHub repository"
description: "7 papers in the tracked journals link to the GitHub repository makcedward/nlpaug in their Crossref records, the first in 2022; most of them (4) in 2024."
url: https://scholar4ai.com/code/github-makcedward-nlpaug
markdown_url: https://scholar4ai.com/code/github-makcedward-nlpaug.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "7 papers in the tracked journals link to the GitHub repository makcedward/nlpaug in their Crossref records, the first in 2022; most of them (4) in 2024. (as of 2026-11-03)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-03T14:43:26+09:00
window: 2026-10-05 to 2026-11-03
source: OpenAlex (CC0)
---

# makcedward/nlpaug: papers linking to it

Research papers in the 480 tracked journals that link to makcedward/nlpaug (https://github.com/makcedward/nlpaug), read from their Crossref records: by year, category and journal, the family tree of papers building on one another, and the linked repositories derived from it or that it derives from.

- GitHub
- 4,664 stars
- 471 forks
- Jupyter Notebook
- license MIT
- created 2019
- https://github.com/makcedward/nlpaug

All repositories: https://scholar4ai.com/code.md

## Key findings

- 7 papers in the tracked journals link to the GitHub repository makcedward/nlpaug in their Crossref records, the first in 2022; most of them (4) in 2024.
- By category: AI (7); the journals with the most are Knowledge and Information Systems (2), International Journal of Computer Vision (1) and Cognitive Computation (1).

## By year

*Papers linking to makcedward/nlpaug by publication year*

| Year | Papers |
|---|---:|
| 2022 | 1 |
| 2024 | 4 |
| 2025 | 2 |

## Journals

*Journals whose papers link to makcedward/nlpaug most*

| Journal | Papers |
|---|---:|
| [Knowledge and Information Systems](https://scholar4ai.com/journals/knowledge-and-information-systems.md) | 2 |
| [International Journal of Computer Vision](https://scholar4ai.com/journals/international-journal-of-computer-vision.md) | 1 |
| [Cognitive Computation](https://scholar4ai.com/journals/cognitive-computation.md) | 1 |
| [Language Resources and Evaluation](https://scholar4ai.com/journals/language-resources-and-evaluation.md) | 1 |
| [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | 1 |

## Papers

*Papers linking to makcedward/nlpaug, most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2022-07-09 | [Twin Contrastive Learning for Online Clustering](https://doi.org/10.1007/s11263-022-01639-z) | [International Journal of Computer Vision](https://scholar4ai.com/journals/international-journal-of-computer-vision.md) | Yunfan Li, Mouxing Yang, Dezhong Peng et al. | 152 | cites it |
| 2024-08-06 | [Explainable AI for Text Classification: Lessons from a Comprehensive Evaluation of Post Hoc Methods](https://doi.org/10.1007/s12559-024-10325-w) | [Cognitive Computation](https://scholar4ai.com/journals/cognitive-computation.md) | Mirko Cesarini, Lorenzo Malandri, Filippo Pallucchini et al. | 36 | cites it |
| 2024-06-13 | [Advancing machine learning with OCR2SEQ: an innovative approach to multi-modal data augmentation](https://doi.org/10.1186/s40537-024-00927-4) | [Journal Of Big Data](https://scholar4ai.com/journals/journal-of-big-data.md) | Michael Lowe, Joseph D. Prusa, Joffrey L. Leevy et al. | 4 | cites it |
| 2024-11-20 | [Key-based data augmentation with curriculum learning for few-shot code search](https://doi.org/10.1007/s00521-024-10670-9) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | Fan Zhang, Manman Peng, Qiang Wu et al. | 3 | cites it |
| 2025-10-14 | [Learning to rank under uncertainty: a robust neural approach](https://doi.org/10.1007/s10115-025-02601-4) | [Knowledge and Information Systems](https://scholar4ai.com/journals/knowledge-and-information-systems.md) | Maryam Khodabakhsh, Ebrahim Bagheri A | 2 | cites it |
| 2024-04-11 | [Adaptive semi-supervised learning from stronger augmentation transformations of discrete text information](https://doi.org/10.1007/s10115-024-02100-y) | [Knowledge and Information Systems](https://scholar4ai.com/journals/knowledge-and-information-systems.md) | Xuemiao Zhang, Zhouxing Tan, Fengyu Lu et al. | 1 | cites it |
| 2025-07-08 | [Enhancing software and learning with Serbian student feedback corpora](https://doi.org/10.1007/s10579-025-09855-y) | [Language Resources and Evaluation](https://scholar4ai.com/journals/language-resources-and-evaluation.md) | Dragan Vidaković, Nikola Luburić, Aleksandar Kovačević et al. | 0 | cites it |

## How this is measured

Links are read from each paper's Crossref record as its publisher deposited it: the URLs and repository DOIs in its reference list (the software and data it cites) and its supplementary links (“is-supplemented-by”: its own code or data). A paper that gives its code only in the text, a footnote or a data availability statement is not counted, and some publishers deposit reference lists without their URLs, so every count here is a lower bound. Repository details come from the GitHub REST API (stars, forks, and the repository a fork was made from), the Hugging Face Hub API (likes, downloads, and the base model a model was derived from) and DataCite (Zenodo and other data DOIs, and the GitHub release a Zenodo record archives), read again every month.

## Cite this page

Scholar4AI. (2026). makcedward/nlpaug: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-makcedward-nlpaug

```bibtex
@misc{scholar4ai-code-github-makcedward-nlpaug,
  author = {{Scholar4AI}},
  title = {makcedward/nlpaug: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/github-makcedward-nlpaug}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}
```

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).