Unsupervised Contrastive Graph Kolmogorov–Arnold Networks Enhanced Cross-Modal Retrieval Hashing
To address modality heterogeneity and accelerate large-scale retrieval, cross-modal hashing strategies generate compact binary codes that enhance computational efficiency. Existing approaches often struggle with suboptimal feature learning due to fixed activation functions and limited cross-modal in...
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MDPI AG
2025-06-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/13/11/1880 |
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| author | Hongyu Lin Shaofeng Shen Yuchen Zhang Renwei Xia |
| author_facet | Hongyu Lin Shaofeng Shen Yuchen Zhang Renwei Xia |
| author_sort | Hongyu Lin |
| collection | DOAJ |
| description | To address modality heterogeneity and accelerate large-scale retrieval, cross-modal hashing strategies generate compact binary codes that enhance computational efficiency. Existing approaches often struggle with suboptimal feature learning due to fixed activation functions and limited cross-modal interaction. We propose Unsupervised Contrastive Graph Kolmogorov–Arnold Networks (GraphKAN) Enhanced Cross-modal Retrieval Hashing (UCGKANH), integrating GraphKAN with contrastive learning and hypergraph-based enhancement. GraphKAN enables more flexible cross-modal representation through enhanced nonlinear expression of features. We introduce contrastive learning that captures modality-invariant structures through sample pairs. To preserve high-order semantic relations, we construct a hypergraph-based information propagation mechanism, refining hash codes by enforcing global consistency. The efficacy of our UCGKANH approach is validated by thorough tests on the MIR-FLICKR, NUS-WIDE, and MS COCO datasets, which show significant gains in retrieval accuracy coupled with strong computational efficiency. |
| format | Article |
| id | doaj-art-3947e4f6602f4c9ba10e55d1d45f3e64 |
| institution | OA Journals |
| issn | 2227-7390 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj-art-3947e4f6602f4c9ba10e55d1d45f3e642025-08-20T02:23:04ZengMDPI AGMathematics2227-73902025-06-011311188010.3390/math13111880Unsupervised Contrastive Graph Kolmogorov–Arnold Networks Enhanced Cross-Modal Retrieval HashingHongyu Lin0Shaofeng Shen1Yuchen Zhang2Renwei Xia3Dundee International Institute of Central South University, Central South University, Changsha 410083, ChinaSchool of Computer Science and Engineering, Central South University, Changsha 410083, ChinaSchool of Computer Science and Engineering, Central South University, Changsha 410083, ChinaSchool of Computer Science and Engineering, Central South University, Changsha 410083, ChinaTo address modality heterogeneity and accelerate large-scale retrieval, cross-modal hashing strategies generate compact binary codes that enhance computational efficiency. Existing approaches often struggle with suboptimal feature learning due to fixed activation functions and limited cross-modal interaction. We propose Unsupervised Contrastive Graph Kolmogorov–Arnold Networks (GraphKAN) Enhanced Cross-modal Retrieval Hashing (UCGKANH), integrating GraphKAN with contrastive learning and hypergraph-based enhancement. GraphKAN enables more flexible cross-modal representation through enhanced nonlinear expression of features. We introduce contrastive learning that captures modality-invariant structures through sample pairs. To preserve high-order semantic relations, we construct a hypergraph-based information propagation mechanism, refining hash codes by enforcing global consistency. The efficacy of our UCGKANH approach is validated by thorough tests on the MIR-FLICKR, NUS-WIDE, and MS COCO datasets, which show significant gains in retrieval accuracy coupled with strong computational efficiency.https://www.mdpi.com/2227-7390/13/11/1880cross-modal retrievalhashingGraph Kolmogorov–Arnold Networkscontrastive learninghypergraph neural networks |
| spellingShingle | Hongyu Lin Shaofeng Shen Yuchen Zhang Renwei Xia Unsupervised Contrastive Graph Kolmogorov–Arnold Networks Enhanced Cross-Modal Retrieval Hashing Mathematics cross-modal retrieval hashing Graph Kolmogorov–Arnold Networks contrastive learning hypergraph neural networks |
| title | Unsupervised Contrastive Graph Kolmogorov–Arnold Networks Enhanced Cross-Modal Retrieval Hashing |
| title_full | Unsupervised Contrastive Graph Kolmogorov–Arnold Networks Enhanced Cross-Modal Retrieval Hashing |
| title_fullStr | Unsupervised Contrastive Graph Kolmogorov–Arnold Networks Enhanced Cross-Modal Retrieval Hashing |
| title_full_unstemmed | Unsupervised Contrastive Graph Kolmogorov–Arnold Networks Enhanced Cross-Modal Retrieval Hashing |
| title_short | Unsupervised Contrastive Graph Kolmogorov–Arnold Networks Enhanced Cross-Modal Retrieval Hashing |
| title_sort | unsupervised contrastive graph kolmogorov arnold networks enhanced cross modal retrieval hashing |
| topic | cross-modal retrieval hashing Graph Kolmogorov–Arnold Networks contrastive learning hypergraph neural networks |
| url | https://www.mdpi.com/2227-7390/13/11/1880 |
| work_keys_str_mv | AT hongyulin unsupervisedcontrastivegraphkolmogorovarnoldnetworksenhancedcrossmodalretrievalhashing AT shaofengshen unsupervisedcontrastivegraphkolmogorovarnoldnetworksenhancedcrossmodalretrievalhashing AT yuchenzhang unsupervisedcontrastivegraphkolmogorovarnoldnetworksenhancedcrossmodalretrievalhashing AT renweixia unsupervisedcontrastivegraphkolmogorovarnoldnetworksenhancedcrossmodalretrievalhashing |