karpathy/nanoGPT: papers linking to it

GitHub · 64,401 stars · 11,066 forks · Python · license MIT · created 2022 · github.com/karpathy/nanoGPT

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to karpathy/nanoGPT (https://github.com/karpathy/nanoGPT), 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 karpathy/nanoGPT in their Crossref records, the first in 2024; most of them (2) in 2026.
By category: AI (2) and Information Systems (1); the journals with the most are Knowledge and Information Systems (1), Electronic Commerce Research (1) and Nature Machine Intelligence (1).

By year#

20242026

Papers linking to karpathy/nanoGPT by publication year
Year	Papers
2024	1
2026	2

Journals#

Journals whose papers link to karpathy/nanoGPT most
Journal	Papers
Knowledge and Information Systems	1
Electronic Commerce Research	1
Nature Machine Intelligence	1

Papers linking to karpathy/nanoGPT, most cited first
Published	Title	Journal	Authors	Citations	Link
2024-11-27	Multimodal language and graph learning of adsorption configuration in catalysis	Nature Machine Intelligence	Janghoon Ock, Srivathsan Badrinarayanan, Rishikesh Magar et al.	42	cites it
2026-04-04	ClickstreamGPT: a transformer-based generative AI approach to clickstream prediction for E-commerce platforms	Electronic Commerce Research	Félipe Mancini, Victor Augusto Sampaio Precoma, Leticia Alves De Oliveira et al.	3	cites it
2026-05-31	Mean activation curvature for scalable second-order optimization in deep networks	Knowledge and Information Systems	Hyunseok Seung, Jaewoo Lee, Hyunsuk Ko	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). karpathy/nanoGPT: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-karpathy-nanogpt

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

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