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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:

Teaching Structured Vision & Language Concepts to Vision & Language Models
Sivan Doveh, Assaf Arbelle, Sivan Harary, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2023), pp. 2657-2668
Closed Access | Times Cited: 23

Showing 23 citing articles:

TMR: Text-to-Motion Retrieval Using Contrastive 3D Human Motion Synthesis
Mathis Petrovich, Michael J. Black, Gül Varol
2021 IEEE/CVF International Conference on Computer Vision (ICCV) (2023)
Open Access | Times Cited: 27
Compositional Chain-of-Thought Prompting for Large Multimodal Models
Chancharik Mitra, Brandon Huang, Trevor Darrell, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2024) Vol. abs/2204.14198, pp. 14420-14431
Closed Access | Times Cited: 7
3VL: Using Trees to Improve Vision-Language Models’ Interpretability
Nir Yellinek, Leonid Karlinsky, Raja Giryes
IEEE Transactions on Image Processing (2025) Vol. 34, pp. 495-509
Open Access
Lang3DSG: Language-based contrastive pre-training for 3D Scene Graph prediction
Sebastian Koch, Pedro Hermosilla, Narunas Vaškevičius, et al.
2021 International Conference on 3D Vision (3DV) (2024) Vol. abs/1512.03012, pp. 1037-1047
Open Access | Times Cited: 3
Zero-Shot Referring Expression Comprehension via Structural Similarity Between Images and Captions
Zeyu Han, Fangrui Zhu, Qianru Lao, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2024), pp. 14364-14375
Closed Access | Times Cited: 3
Open3DSG: Open-Vocabulary 3D Scene Graphs from Point Clouds with Queryable Objects and Open-Set Relationships
Sebastian Koch, Narunas Vaškevičius, Mirco Colosi, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2024), pp. 14183-14193
Closed Access | Times Cited: 1
Generating Enhanced Negatives for Training Language-Based Object Detectors
Shiyu Zhao, L. Zhao, Vijay Kumar B G, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2024) Vol. 9, pp. 13592-13602
Closed Access | Times Cited: 1
ProTeCt: Prompt Tuning for Taxonomic Open Set Classification
Tz-Ying Wu, Chih-Hui Ho, Nuno Vasconcelos
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2024) Vol. abs/2003.04297, pp. 16531-16540
Closed Access | Times Cited: 1
Learning Fine-Grained Information Alignment for Calibrated Cross-Modal Retrieval
Jianhua Dong, Shengrong Zhao, Liang Hu
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (2024), pp. 8286-8290
Closed Access
Synthesize, Diagnose, and Optimize: Towards Fine-Grained Vision-Language Understanding
Wujian Peng, Sicheng Xie, Zuyao You, et al.
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2024), pp. 13279-13288
Closed Access
Domain Alignment with Large Vision-language Models for Cross-domain Remote Sensing Image Retrieval
Yan Chen, Guocan Cai, Fufang Li, et al.
(2024), pp. 323-333
Closed Access
Removing Distributional Discrepancies in Captions Improves Image-Text Alignment
Yuheng Li, Haotian Liu, Mu Cai, et al.
Lecture notes in computer science (2024), pp. 405-422
Closed Access
Fact :Teaching MLLMs with <u>Fa</u>ithful, <u>C</u>oncise and <u>T</u>ransferable Rationales
Minghe Gao, Shouxu Chen, Liang Pang, et al.
(2024), pp. 846-855
Closed Access
Weak-to-Strong Compositional Learning from Generative Models for Language-Based Object Detection
Kwanyong Park, Kuniaki Saito, Donghyun Kim
Lecture notes in computer science (2024), pp. 1-19
Closed Access
The Hard Positive Truth About Vision-Language Compositionality
Amita Kamath, Cheng-Yu Hsieh, Kai-Wei Chang, et al.
Lecture notes in computer science (2024), pp. 37-54
Closed Access
Improving Vision and Language Concepts Understanding with Multimodal Counterfactual Samples
Chengen Lai, Shengli Song, Sitong Yan, et al.
Lecture notes in computer science (2024), pp. 174-191
Closed Access
Capture Concept Through Comparison: Vision-and-Language Representation Learning with Intrinsic Information Mining
Yun-Zhu Song, Yi-Syuan Chen, Tzu-Ling Lin, et al.
Lecture notes in computer science (2024), pp. 220-238
Closed Access
Investigating the Role of Attribute Context in Vision-Language Models for Object Recognition and Detection
Kyle Buettner, Adriana Kovashka
2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) (2024), pp. 5462-5472
Open Access
Enhancing Multimodal Compositional Reasoning of Visual Language Models with Generative Negative Mining
Uğur Şahin, Hang Li, Qadeer Khan, et al.
2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) (2024), pp. 5551-5561
Open Access
Contrasting Intra-Modal and Ranking Cross-Modal Hard Negatives to Enhance Visio-Linguistic Compositional Understanding
Le Zhang, Rabiul Awal, Aishwarya Agrawal
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2024) Vol. 33, pp. 13774-13784
Closed Access
Learning by Correction: Efficient Tuning Task for Zero-Shot Generative Vision-Language Reasoning
Rongjie Li, Yu Wu, Xuming He
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2024) Vol. 35, pp. 13428-13437
Closed Access
MSKR: Advancing Multi-modal Structured Knowledge Representation with Synergistic Hard Negative Samples
S. F. Zhang, Hongzhang Mu, Tingwen Liu, et al.
(2024), pp. 3207-3216
Closed Access
Enhancing CLIP-Based Text-Person Retrieval by Leveraging Negative Samples
Yumin Tian, Yuanbo Li, Di Wang, et al.
Lecture notes in computer science (2023), pp. 271-283
Closed Access
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