chakki-works/seqeval: papers linking to it

GitHub · 1,188 stars · 132 forks · Python · license MIT · created 2018 · github.com/chakki-works/seqeval

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to chakki-works/seqeval (https://github.com/chakki-works/seqeval), 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 chakki-works/seqeval in their Crossref records, the first in 2023; most of them (1) in 2025.
By category: AI (3); the journals with the most are Language Resources and Evaluation (2) and Neural Computing and Applications (1).

By year#

20232025

Papers linking to chakki-works/seqeval by publication year
Year	Papers
2023	1
2024	1
2025	1

Journals#

Journals whose papers link to chakki-works/seqeval most
Journal	Papers
Language Resources and Evaluation	2
Neural Computing and Applications	1

Papers linking to chakki-works/seqeval, most cited first
Published	Title	Journal	Authors	Citations	Link
2023-05-20	EduNER: a Chinese named entity recognition dataset for education research	Neural Computing and Applications	Xu Li, Chengkun Wei, Zhuoren Jiang et al.	16	cites it
2024-01-13	Toxic comment classification and rationale extraction in code-mixed text leveraging co-attentive multi-task learning	Language Resources and Evaluation	Kiran Babu Nelatoori, K. Hima Bindu	12	cites it
2025-12-26	Tenyidie named entity recognition: corpus creation and machine/deep learning applications	Language Resources and Evaluation	Teisovi Angami, Themrichon Tuithung	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). chakki-works/seqeval: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-chakki-works-seqeval

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

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