huggingface/accelerate: papers linking to it

GitHub · 9,935 stars · 1,589 forks · Python · license Apache-2.0 · created 2020 · github.com/huggingface/accelerate

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to huggingface/accelerate (https://github.com/huggingface/accelerate), 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 huggingface/accelerate in their Crossref records, the first in 2025; most of them (2) in 2025.
By category: AI (3); the journals with the most are Expert Systems with Applications (2) and International Journal of Computer Vision (1).

By year#

20252026

Papers linking to huggingface/accelerate by publication year
Year	Papers
2025	2
2026	1

Journals#

Journals whose papers link to huggingface/accelerate most
Journal	Papers
Expert Systems with Applications	2
International Journal of Computer Vision	1

Papers linking to huggingface/accelerate, most cited first
Published	Title	Journal	Authors	Citations	Link
2025-10-31	ITGO: A general framework for text-guided image outpainting	Expert Systems with Applications	Bin Chen, Yuanbo Zhou, Xinlin Zhang et al.	1	cites it
2026-02-21	Diffusion-Based Data Augmentation for Image Recognition: A Systematic Analysis and Evaluation	International Journal of Computer Vision	Zekun Li, Yinghuan Shi, Yang Gao et al.	1	cites it
2025-12-11	Semantic parsing with candidate expressions for knowledge base question answering	Expert Systems with Applications	Daehwan Nam, Gary Geunbae Lee	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). huggingface/accelerate: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-huggingface-accelerate

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

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