Scholar4AI Updated 2026-11-03 14:43 UTC+09:00

huggingface/peft: papers linking to it

GitHub · 21,869 stars · 2,645 forks · Python · license Apache-2.0 · created 2022 · github.com/huggingface/peft

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to huggingface/peft (https://github.com/huggingface/peft), 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.

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Key findings#

  • 10 papers in the tracked journals link to the GitHub repository huggingface/peft in their Crossref records, the first in 2024; most of them (5) in 2026.
  • By category: AI (10); the journals with the most are Neural Networks (2), Nature Machine Intelligence (2) and Knowledge-Based Systems (1).

By year#

2024: 1 paper2025: 4 papers2026: 5 papers
20242026
Papers linking to huggingface/peft by publication year
YearPapers
20241
20254
20265

Journals#

Papers linking to huggingface/peft, most cited first
PublishedTitleJournalAuthorsCitationsLink
2025-08-09LoRA dropout as a sparsity regularizer for overfitting reductionKnowledge-Based SystemsYang Lin, Xinyu Ma, Xu Chu et al.19cites it
2024-10-03Engineering flexible machine learning systems by traversing functionally invariant pathsNature Machine IntelligenceGuruprasad Raghavan, Bahey Tharwat, Surya N. Hari et al.13cites it
2026-09-25Parameter-Efficient Fine-Tuning for Foundation ModelsInternational Journal of Computer VisionDan Zhang, Tao Feng, Lilong Xue et al.7cites it
2025-04-18Endless forms most similar: the dearth of the author in AI-supported artAI & SocietyMax Kreminski4cites it
2025-12-05RaLo: Rank-aware low-rank adaptation for pre-trained foundation modelsNeural NetworksYunsong Deng, Guoxu Zhou, Qibin Zhao3cites it
2026-01-29A survey On large language models for medical time seriesExpert Systems with ApplicationsXingyue Liu, Feizhong Zhou, Hanguang Xiao et al.2cites it
2026-04-01Predicting new research directions in materials science using large language models and concept graphsNature Machine IntelligenceThomas Marwitz, Alexander Colsmann, Ben Breitung et al.2cites it
2025-12-26From 2D Images to 3D Model: Segmenting and Reconstructing Acne for Robust Skin Lesion AnalysisCognitive ComputationChengrui Zhang, Zhaorui Tan, Xi Yang et al.1cites it
2026-05-08A comprehensive review of use cases, misuses, and potential mitigation techniques in generative artificial intelligenceNeural NetworksKalp Patel, Rishi Ajith, Surendrabikram Thapa et al.1cites it
2026-03-12Capability of large language models in assisting GPs with diagnosesApplied IntelligenceRuibin Wang, Abdul Rehman, Tingting Li et al.0cites 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/peft: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-huggingface-peft

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

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