---
title: "openai/CLIP: papers citing this GitHub repository"
description: "3 papers in the tracked journals link to the GitHub repository openai/CLIP in their Crossref records, the first in 2024; most of them (2) in 2025."
url: https://scholar4ai.com/code/github-openai-clip
markdown_url: https://scholar4ai.com/code/github-openai-clip.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "3 papers in the tracked journals link to the GitHub repository openai/CLIP in their Crossref records, the first in 2024; most of them (2) in 2025. (as of 2026-11-03)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-03T14:43:26+09:00
window: 2026-10-05 to 2026-11-03
source: OpenAlex (CC0)
---

# openai/CLIP: papers linking to it

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

- GitHub
- 34,560 stars
- 4,063 forks
- Jupyter Notebook
- license MIT
- created 2020
- https://github.com/openai/CLIP

All repositories: https://scholar4ai.com/code.md

## Key findings

- 3 papers in the tracked journals link to the GitHub repository openai/CLIP in their Crossref records, the first in 2024; most of them (2) in 2025.
- By category: AI (3); the journals with the most are Knowledge-Based Systems (1), Nature Machine Intelligence (1) and International Journal of Computer Vision (1).

## By year

*Papers linking to openai/CLIP by publication year*

| Year | Papers |
|---|---:|
| 2024 | 1 |
| 2025 | 2 |

## Journals

*Journals whose papers link to openai/CLIP most*

| Journal | Papers |
|---|---:|
| [Knowledge-Based Systems](https://scholar4ai.com/journals/knowledge-based-systems.md) | 1 |
| [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | 1 |
| [International Journal of Computer Vision](https://scholar4ai.com/journals/international-journal-of-computer-vision.md) | 1 |

## Papers

*Papers linking to openai/CLIP, most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2025-03-17 | [Explainable AI reveals Clever Hans effects in unsupervised learning models](https://doi.org/10.1038/s42256-025-01000-2) | [Nature Machine Intelligence](https://scholar4ai.com/journals/nature-machine-intelligence.md) | Jacob Kauffmann, Jonas Dippel, Lukas Ruff et al. | 35 | cites it |
| 2024-01-12 | [Generative Adversarial Network Applications in Industry 4.0: A Review](https://doi.org/10.1007/s11263-023-01966-9) | [International Journal of Computer Vision](https://scholar4ai.com/journals/international-journal-of-computer-vision.md) | Chafic Abou Akar, Rachelle Abdel Massih, Anthony Yaghi et al. | 31 | cites it |
| 2025-02-14 | [LLM Knowledge-Driven Target Prototype Learning for Few-Shot Segmentation](https://doi.org/10.1016/j.knosys.2025.113149) | [Knowledge-Based Systems](https://scholar4ai.com/journals/knowledge-based-systems.md) | Pengfang Li, Fang Liu, Licheng Jiao et al. | 12 | 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). openai/CLIP: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-openai-clip

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

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).