kaonashi-tyc/zi2zi: papers linking to it

GitHub · 2,755 stars · 475 forks · Python · license Apache-2.0 · created 2017 · github.com/kaonashi-tyc/zi2zi

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to kaonashi-tyc/zi2zi (https://github.com/kaonashi-tyc/zi2zi), 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 kaonashi-tyc/zi2zi in their Crossref records, the first in 2025; most of them (2) in 2026.
By category: AI (3); the journals with the most are Knowledge-Based Systems (2) and Neural Networks (1).
2 of the papers build on one another: a later paper cites an earlier one that also links kaonashi-tyc/zi2zi.

By year#

20252026

Papers linking to kaonashi-tyc/zi2zi by publication year
Year	Papers
2025	1
2026	2

Journals#

Journals whose papers link to kaonashi-tyc/zi2zi most
Journal	Papers
Knowledge-Based Systems	2
Neural Networks	1

Family tree#

Each paper sits under the earlier paper it builds on; papers that cite no other paper here start a branch of their own.

SGD-font: Style and glyph decoupling for one-shot font generation Knowledge-Based Systems, 2025
- Fontify : One-shot font generation via in-context learning Knowledge-Based Systems, 2026 — cites the paper above

Papers linking to kaonashi-tyc/zi2zi, most cited first
Published	Title	Journal	Authors	Citations	Link
2025-10-11	SGD-font: Style and glyph decoupling for one-shot font generation	Knowledge-Based Systems	Zhenhua Li, Siyi Chen, Dong Liang	4	cites it
2026-01-18	Fontify : One-shot font generation via in-context learning	Knowledge-Based Systems	Ying Xu, Xiangwei Zhu, Songyuan Li	1	cites it
2026-03-13	DBML-Font :Double-branch multi-level feature fusion based on diffusion model for few-shot font generation	Neural Networks	Yueyue Fang, Haipeng Xiao, Wenyi Zhou 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). kaonashi-tyc/zi2zi: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-kaonashi-tyc-zi2zi

@misc{scholar4ai-code-github-kaonashi-tyc-zi2zi,
  author = {{Scholar4AI}},
  title = {kaonashi-tyc/zi2zi: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/github-kaonashi-tyc-zi2zi}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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