--- title: "OpenCLIP: papers citing this dataset" description: "13 papers in the tracked journals link to the Zenodo dataset OpenCLIP in their Crossref records, the first in 2023; most of them (5) in 2026." url: https://scholar4ai.com/code/zenodo-5143773 markdown_url: https://scholar4ai.com/code/zenodo-5143773.md license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/) share_text: "13 papers in the tracked journals link to the Zenodo dataset OpenCLIP in their Crossref records, the first in 2023; most of them (5) in 2026. (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) --- # OpenCLIP: papers linking to it Research papers in the 480 tracked journals that link to OpenCLIP (https://doi.org/10.5281/zenodo.5143773), 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. - Zenodo - Software - 2021 - archives github.com/mlfoundations/open_clip - https://doi.org/10.5281/zenodo.5143773 All repositories: https://scholar4ai.com/code.md ## Key findings - 13 papers in the tracked journals link to the Zenodo dataset OpenCLIP in their Crossref records, the first in 2023; most of them (5) in 2026. - By category: AI (13); the journals with the most are International Journal of Computer Vision (8), Expert Systems with Applications (2) and Neural Networks (1). - It is a Zenodo archive of mlfoundations/open_clip, which other papers here link to as well. ## By year *Papers linking to OpenCLIP by publication year* | Year | Papers | |---|---:| | 2023 | 1 | | 2024 | 2 | | 2025 | 5 | | 2026 | 5 | ## Journals *Journals whose papers link to OpenCLIP most* | Journal | Papers | |---|---:| | [International Journal of Computer Vision](https://scholar4ai.com/journals/international-journal-of-computer-vision.md) | 8 | | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | 2 | | [Neural Networks](https://scholar4ai.com/journals/neural-networks.md) | 1 | | [Machine Learning](https://scholar4ai.com/journals/machine-learning.md) | 1 | | [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | 1 | ## Related repositories *Linked repositories OpenCLIP derives from or that derive from it* | Repository | Relation | Papers | |---|---|---:| | [mlfoundations/open_clip](https://github.com/mlfoundations/open_clip) | OpenCLIP is its Zenodo archive | 1 | ## Papers *Papers linking to OpenCLIP, most cited first* | Published | Title | Journal | Authors | Citations | Link | |---|---|---|---|---:|---| | 2024-09-19 | [FastComposer: Tuning-Free Multi-subject Image Generation with Localized Attention](https://doi.org/10.1007/s11263-024-02227-z) | [International Journal of Computer Vision](https://scholar4ai.com/journals/international-journal-of-computer-vision.md) | Guangxuan Xiao, Tianwei Yin, William T. Freeman et al. | 167 | cites it | | 2024-08-09 | [A Comprehensive Study on Robustness of Image Classification Models: Benchmarking and Rethinking](https://doi.org/10.1007/s11263-024-02196-3) | [International Journal of Computer Vision](https://scholar4ai.com/journals/international-journal-of-computer-vision.md) | Chang Liu, Yinpeng Dong, Wenzhao Xiang et al. | 104 | cites it | | 2023-12-03 | [Context-Aware Robust Fine-Tuning](https://doi.org/10.1007/s11263-023-01951-2) | [International Journal of Computer Vision](https://scholar4ai.com/journals/international-journal-of-computer-vision.md) | Xiaofeng Mao, Yufeng Chen, Xiaojun Jia et al. | 23 | cites it | | 2025-02-18 | [VideoQA in the Era of LLMs: An Empirical Study](https://doi.org/10.1007/s11263-025-02385-8) | [International Journal of Computer Vision](https://scholar4ai.com/journals/international-journal-of-computer-vision.md) | Junbin Xiao, Nanxin Huang, Hangyu Qin et al. | 16 | cites it | | 2025-01-28 | [Learning with Enriched Inductive Biases for Vision-Language Models](https://doi.org/10.1007/s11263-025-02354-1) | [International Journal of Computer Vision](https://scholar4ai.com/journals/international-journal-of-computer-vision.md) | Lingxiao Yang, Ru‐Yuan Zhang, Qi Chen et al. | 11 | cites it | | 2025-12-10 | [Learn from foundation model: Fruit detection model without manual annotation](https://doi.org/10.1016/j.patcog.2025.112799) | [Pattern Recognition](https://scholar4ai.com/journals/pattern-recognition.md) | Yanan Wang, Zhenghao Fei, Ruichen Li et al. | 7 | cites it | | 2026-02-12 | [EgoPlan-Bench: Benchmarking Multimodal Large Language Models for Human-Level Planning](https://doi.org/10.1007/s11263-025-02676-0) | [International Journal of Computer Vision](https://scholar4ai.com/journals/international-journal-of-computer-vision.md) | Yuehua Chen, Yuying Ge, Yixiao Ge et al. | 7 | cites it | | 2025-06-20 | [Training-free, Identity-preserving Image Editing for Fashion Pose Alignment and Normalization](https://doi.org/10.1016/j.eswa.2025.128579) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Potito Aghilar, Vito Walter Anelli, Michelantonio Trizio et al. | 4 | cites it | | 2026-03-26 | [Guidelines for the selection, calibration, and evaluation of post-hoc OOD detectors in high-dimensional representations generated by CNN and ViT models in image recognition](https://doi.org/10.1016/j.eswa.2026.132191) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | Szymon Datko, Kamil Szyc, Tomasz Walkowiak et al. | 1 | cites it | | 2025-02-24 | [Uncover the balanced geometry in long-tailed contrastive language-image pretraining](https://doi.org/10.1007/s10994-025-06745-w) | [Machine Learning](https://scholar4ai.com/journals/machine-learning.md) | Zhihan Zhou, Yushi Ye, Feng Hong et al. | 0 | cites it | | 2026-03-09 | [Towards Scene-Aware Video-to-Spatial Audio Generation](https://doi.org/10.1007/s11263-025-02610-4) | [International Journal of Computer Vision](https://scholar4ai.com/journals/international-journal-of-computer-vision.md) | Jaeyeon Kim, Heeseung Yun, Gunhee Kim | 0 | cites it | | 2026-04-30 | [Semantic clustering under resource constraints via Bayesian low-rank adaptation](https://doi.org/10.1016/j.neunet.2026.109021) | [Neural Networks](https://scholar4ai.com/journals/neural-networks.md) | Minda Yu, Xulun Ye | 0 | cites it | | 2026-08-01 | [GUIDED++: Enhancing Discrimination with Conjunctive Verification for Fine-Grained Open-Vocabulary Object Detection](https://doi.org/10.1007/s11263-026-02986-x) | [International Journal of Computer Vision](https://scholar4ai.com/journals/international-journal-of-computer-vision.md) | Jiaming Li, Zhijia Liang, Shuangyin Liu 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). OpenCLIP: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/zenodo-5143773 ```bibtex @misc{scholar4ai-code-zenodo-5143773, author = {{Scholar4AI}}, title = {OpenCLIP: papers linking to it}, year = {2026}, howpublished = {\url{https://scholar4ai.com/code/zenodo-5143773}}, 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/).