ThilinaRajapakse/simpletransformers: papers linking to it

GitHub · 4,257 stars · 709 forks · Python · license Apache-2.0 · created 2019 · github.com/ThilinaRajapakse/simpletransformers

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to ThilinaRajapakse/simpletransformers (https://github.com/ThilinaRajapakse/simpletransformers), 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#

3 papers in the tracked journals link to the GitHub repository ThilinaRajapakse/simpletransformers in their Crossref records, the first in 2021; most of them (2) in 2021.
By category: Information Systems (1), Higher Education and Research (1) and AI (1); the journals with the most are Information Systems Frontiers (1), Scientometrics (1) and Neural Computing and Applications (1).

By year#

20212024

Papers linking to ThilinaRajapakse/simpletransformers by publication year
Year	Papers
2021	2
2024	1

Journals#

Journals whose papers link to ThilinaRajapakse/simpletransformers most
Journal	Papers
Information Systems Frontiers	1
Scientometrics	1
Neural Computing and Applications	1

Papers linking to ThilinaRajapakse/simpletransformers, most cited first
Published	Title	Journal	Authors	Citations	Link
2021-12-17	PatentNet: multi-label classification of patent documents using deep learning based language understanding	Scientometrics	Arousha Haghighian Roudsari, Jafar Afshar, Wookey Lee et al.	93	cites it
2021-10-29	Using weak supervision to generate training datasets from social media data: a proof of concept to identify drug mentions	Neural Computing and Applications	Ramya Tekumalla, Juan M. Banda	19	cites it
2024-09-24	Combating Online Malicious Behavior: Integrating Machine Learning and Deep Learning Methods for Harmful News and Toxic Comments	Information Systems Frontiers	Szu‐Yin Lin, Shih-Yi James Chien, Yi-Zhen Chen et al.	6	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). ThilinaRajapakse/simpletransformers: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-thilinarajapakse-simpletransformers

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

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