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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Not All Features Matter: Enhancing Few-shot CLIP with Adaptive Prior Refinement
Xiangyang Zhu, Renrui Zhang, Bowei He, et al.
2021 IEEE/CVF International Conference on Computer Vision (ICCV) (2023), pp. 2605-2615
Open Access | Times Cited: 16

Showing 16 citing articles:

Ta-Adapter: Enhancing few-shot CLIP with task-aware encoders
Wenbo Zhang, Yifan Zhang, Yuyang Deng, et al.
Pattern Recognition (2024) Vol. 153, pp. 110559-110559
Closed Access | Times Cited: 8
A Slim Prompt-Averaged Consistency prompt learning for vision-language model
Siyu He, Shengsheng Wang, Sifan Long
Knowledge-Based Systems (2025), pp. 113011-113011
Closed Access
Supporting vision-language model few-shot inference with confounder-pruned knowledge prompt
Jiangmeng Li, Wenyi Mo, Song Fei, et al.
Neural Networks (2025) Vol. 185, pp. 107173-107173
Closed Access
Self-assembled Generative Framework for Generalized Zero-shot Learning
Mengyu Gao, Qiulei Dong
IEEE Transactions on Image Processing (2025) Vol. 34, pp. 914-924
Closed Access
PlantCaFo: An efficient few-shot plant disease recognition method based on foundation models
Xue Jiang, Jianwei Wang, Kai Xie, et al.
Plant Phenomics (2025), pp. 100024-100024
Open Access
FILP-3D: Enhancing 3D few-shot class-incremental learning with pre-trained vision-language models
Wan Xu, Tianyu Huang, Tianyuan Qu, et al.
Pattern Recognition (2025), pp. 111558-111558
Closed Access
DeIL: Direct-and-Inverse CLIP for Open-World Few-Shot Learning
Shuai Shao, Yu Bai, Yan Wang, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2024) Vol. 32, pp. 28505-28514
Closed Access | Times Cited: 3
Gradient-based Parameter Selection for Efficient Fine-Tuning
Zhi Zhang, Qizhe Zhang, Zijun Gao, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2024) Vol. abs/2007.12223, pp. 28566-28577
Closed Access | Times Cited: 2
MoPE-CLIP: Structured Pruning for Efficient Vision-Language Models with Module-Wise Pruning Error Metric
Haokun Lin, Haoli Bai, Zhili Liu, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2024) Vol. 34, pp. 27360-27370
Closed Access | Times Cited: 2
Frequency-Aware Multi-Modal Fine-Tuning for Few-Shot Open-Set Remote Sensing Scene Classification
Junjie Zhang, Yutao Rao, Xiaoshui Huang, et al.
IEEE Transactions on Multimedia (2024) Vol. 26, pp. 7823-7837
Closed Access | Times Cited: 1
Dr. CLIP: CLIP-Driven Universal Framework for Zero-Shot Sketch Image Retrieval
Xue Li, Jiong Yu, Ziyang Li, et al.
(2024), pp. 9554-9562
Closed Access | Times Cited: 1
Label Propagation for Zero-shot Classification with Vision-Language Models
Vladan Stojnić, Yannis Kalantidis, Giorgos Tolias
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2024) Vol. 9, pp. 23209-23218
Closed Access
Multi-layer Tuning CLIP for Few-Shot Image Classification
Ruihao Zhang, Jinsong Geng, Chengyuan Liu, et al.
Lecture notes in computer science (2024), pp. 173-186
Closed Access
One-shot In-context Part Segmentation
Zhen li Dai, Ting Liu, Xingxing Zhang, et al.
(2024), pp. 10966-10975
Closed Access
Few-Shot Image Classification of Crop Diseases Based on Vision–Language Models
Yueyue Zhou, Hongping Yan, Kun Ding, et al.
Sensors (2024) Vol. 24, Iss. 18, pp. 6109-6109
Open Access
WaveDN: A Wavelet-based Training-free Zero-shot Enhancement for Vision-Language Models
J M Li, Mengyu Yang, Ye Tian, et al.
(2024), pp. 4273-4282
Closed Access
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