makcedward/nlpaug: papers linking to it

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

← Code and data repositories cited in research papers

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.

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#

20222025

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	2
International Journal of Computer Vision	1
Cognitive Computation	1
Language Resources and Evaluation	1
Neural Computing and Applications	1

Papers linking to makcedward/nlpaug, most cited first
Published	Title	Journal	Authors	Citations	Link
2022-07-09	Twin Contrastive Learning for Online Clustering	International Journal of Computer Vision	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	Cognitive Computation	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	Journal Of Big Data	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	Neural Computing and Applications	Fan Zhang, Manman Peng, Qiang Wu et al.	3	cites it
2025-10-14	Learning to rank under uncertainty: a robust neural approach	Knowledge and Information Systems	Maryam Khodabakhsh, Ebrahim Bagheri A	2	cites it
2024-04-11	Adaptive semi-supervised learning from stronger augmentation transformations of discrete text information	Knowledge and Information Systems	Xuemiao Zhang, Zhouxing Tan, Fengyu Lu et al.	1	cites it
2025-07-08	Enhancing software and learning with Serbian student feedback corpora	Language Resources and Evaluation	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

@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}
}

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