{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T15:14:43Z","timestamp":1783696483444,"version":"3.55.0"},"reference-count":38,"publisher":"Elsevier BV","issue":"7","license":[{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Information Processing & Management"],"published-print":{"date-parts":[[2026,11]]},"DOI":"10.1016\/j.ipm.2026.104865","type":"journal-article","created":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T05:08:46Z","timestamp":1777525726000},"page":"104865","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"PB","title":["Hypergraph Kolmogorov\u2013Arnold networks contrastive hashing for unsupervised cross-modal retrieval"],"prefix":"10.1016","volume":"63","author":[{"given":"Zhan","family":"Yang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Boxuan","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Weilu","family":"Long","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-6199-7429","authenticated-orcid":false,"given":"Yunfei","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.ipm.2026.104865_b1","doi-asserted-by":"crossref","first-page":"9418","DOI":"10.1109\/TKDE.2024.3425891","article-title":"Towards effective top-N hamming search via bipartite graph contrastive hashing","author":"Chen","year":"2024","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"issue":"2","key":"10.1016\/j.ipm.2026.104865_b2","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2024.103958","article-title":"Unsupervised Adaptive Hypergraph Correlation Hashing for multimedia retrieval","volume":"62","author":"Chen","year":"2025","journal-title":"Information Processing & Management"},{"key":"10.1016\/j.ipm.2026.104865_b3","doi-asserted-by":"crossref","DOI":"10.1016\/j.neunet.2024.106211","article-title":"Structure-aware contrastive hashing for unsupervised cross-modal retrieval","volume":"174","author":"Cui","year":"2024","journal-title":"Neural Networks"},{"key":"10.1016\/j.ipm.2026.104865_b4","doi-asserted-by":"crossref","unstructured":"Ding, G., Guo, Y., & Zhou, J. (2014). Collective matrix factorization hashing for multimodal data. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 2075\u20132082).","DOI":"10.1109\/CVPR.2014.267"},{"key":"10.1016\/j.ipm.2026.104865_b5","first-page":"2843","article-title":"Vision-guided text mining for unsupervised cross-modal hashing with community similarity quantization","volume":"Vol. 39","author":"Fan","year":"2025"},{"issue":"4","key":"10.1016\/j.ipm.2026.104865_b6","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3632527","article-title":"Supervised hierarchical online hashing for cross-modal retrieval","volume":"20","author":"Han","year":"2024","journal-title":"ACM Transactions on Multimedia Computing, Communications and Applications"},{"issue":"3","key":"10.1016\/j.ipm.2026.104865_b7","first-page":"3877","article-title":"Unsupervised contrastive cross-modal hashing","volume":"45","author":"Hu","year":"2022","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"issue":"4","key":"10.1016\/j.ipm.2026.104865_b8","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2025.104086","article-title":"Effective near-duplicate image detection using perceptual hashing and deep learning","volume":"62","author":"Jakhar","year":"2025","journal-title":"Information Processing & Management"},{"key":"10.1016\/j.ipm.2026.104865_b9","doi-asserted-by":"crossref","unstructured":"Jiang, Q.-Y., & Li, W.-J. (2017). Deep cross-modal hashing. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 3232\u20133240).","DOI":"10.1109\/CVPR.2017.348"},{"issue":"7","key":"10.1016\/j.ipm.2026.104865_b10","doi-asserted-by":"crossref","first-page":"3490","DOI":"10.1109\/TIP.2019.2897944","article-title":"Discrete latent factor model for cross-modal hashing","volume":"28","author":"Jiang","year":"2019","journal-title":"IEEE Transactions on Image Processing"},{"key":"10.1016\/j.ipm.2026.104865_b11","doi-asserted-by":"crossref","unstructured":"Kang, X., Liu, X., Zhang, X., Xue, W., Nie, X., Wang, S., & Yin, Y. (2024). Unsupervised Online Cross-modal Hashing With Multiple Association Exploitation. In 2024 IEEE international conference on multimedia and expo (pp. 1\u20136).","DOI":"10.1109\/ICME57554.2024.10688371"},{"key":"10.1016\/j.ipm.2026.104865_b12","first-page":"1360","article-title":"Learning hash functions for cross-view similarity search","volume":"Vol. 22","author":"Kumar","year":"2011"},{"key":"10.1016\/j.ipm.2026.104865_b13","first-page":"18385","article-title":"Deep hypergraph neural networks with tight framelets","volume":"Vol. 39","author":"Li","year":"2025"},{"issue":"3","key":"10.1016\/j.ipm.2026.104865_b14","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2024.104037","article-title":"Adaptive asymmetric supervised cross-modal hashing with consensus matrix","volume":"62","author":"Li","year":"2025","journal-title":"Information Processing & Management"},{"key":"10.1016\/j.ipm.2026.104865_b15","first-page":"1392","article-title":"Asymmetric cross-modal hashing based on formal concept analysis","volume":"Vol. 39","author":"Li","year":"2025"},{"key":"10.1016\/j.ipm.2026.104865_b16","first-page":"13744","article-title":"Self-supervised multi-modal knowledge graph contrastive hashing for cross-modal search","volume":"Vol. 38","author":"Liang","year":"2024"},{"issue":"3","key":"10.1016\/j.ipm.2026.104865_b17","doi-asserted-by":"crossref","first-page":"964","DOI":"10.1109\/TPAMI.2019.2940446","article-title":"MTFH: A matrix tri-factorization hashing framework for efficient cross-modal retrieval","volume":"43","author":"Liu","year":"2019","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"10.1016\/j.ipm.2026.104865_b18","doi-asserted-by":"crossref","unstructured":"Liu, H., Ji, R., Wu, Y., Huang, F., & Zhang, B. (2017). Cross-modality binary code learning via fusion similarity hashing. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 7380\u20137388).","DOI":"10.1109\/CVPR.2017.672"},{"issue":"12","key":"10.1016\/j.ipm.2026.104865_b19","first-page":"1","article-title":"Fast unsupervised cross-modal hashing with robust factorization and dual projection","volume":"20","author":"Liu","year":"2024","journal-title":"ACM Transactions on Multimedia Computing, Communications and Applications"},{"key":"10.1016\/j.ipm.2026.104865_b20","doi-asserted-by":"crossref","unstructured":"Liu, S., Qian, S., Guan, Y., Zhan, J., & Ying, L. (2020). Joint-modal distribution-based similarity hashing for large-scale unsupervised deep cross-modal retrieval. In Proceedings of the 43rd international ACM SIGIR conference on research and development in information retrieval (pp. 1379\u20131388).","DOI":"10.1145\/3397271.3401086"},{"key":"10.1016\/j.ipm.2026.104865_b21","series-title":"Kan: Kolmogorov-arnold networks","first-page":"24","author":"Liu","year":"2024"},{"key":"10.1016\/j.ipm.2026.104865_b22","doi-asserted-by":"crossref","unstructured":"Lu, X., Zhu, L., Cheng, Z., Li, J., Nie, X., & Zhang, H. (2019). Flexible online multi-modal hashing for large-scale multimedia retrieval. In Proceedings of the 27th ACM international conference on multimedia (pp. 1129\u20131137).","DOI":"10.1145\/3343031.3350999"},{"key":"10.1016\/j.ipm.2026.104865_b23","unstructured":"Prokos, J., Fendley, N., Green, M., Schuster, R., Tromer, E., Jois, T., & Cao, Y. (2023). Squint hard enough: Attacking perceptual hashing with adversarial machine learning. In 32nd USeNIX security symposium (pp. 211\u2013228)."},{"key":"10.1016\/j.ipm.2026.104865_b24","first-page":"44577","article-title":"Cross-modal hashing retrieval based on density clustering","author":"Qi","year":"2020","journal-title":"IEEE Access"},{"key":"10.1016\/j.ipm.2026.104865_b25","doi-asserted-by":"crossref","unstructured":"Su, S., Zhong, Z., & Zhang, C. (2019). Deep joint-semantics reconstructing hashing for large-scale unsupervised cross-modal retrieval. In Proceedings of the IEEE\/CVF international conference on computer vision (pp. 3027\u20133035).","DOI":"10.1109\/ICCV.2019.00312"},{"key":"10.1016\/j.ipm.2026.104865_b26","doi-asserted-by":"crossref","first-page":"2737","DOI":"10.1109\/TIP.2025.3561659","article-title":"Cross-modal hashing via diverse instances matching","author":"Tu","year":"2025","journal-title":"IEEE Transactions on Image Processing"},{"issue":"8","key":"10.1016\/j.ipm.2026.104865_b27","doi-asserted-by":"crossref","first-page":"2765","DOI":"10.1007\/s11263-024-02009-7","article-title":"Hugs bring double benefits: Unsupervised cross-modal hashing with multi-granularity aligned transformers","volume":"132","author":"Wang","year":"2024","journal-title":"International Journal of Computer Vision"},{"key":"10.1016\/j.ipm.2026.104865_b28","doi-asserted-by":"crossref","unstructured":"Wei, R., Cui, H., Liu, Y., Xie, Y., Hou, Y., & Zhou, K. (2024). Contrastive masked auto-encoders based self-supervised hashing for 2D image and 3D point cloud cross-modal retrieval. In 2024 IEEE international conference on multimedia and expo (pp. 1\u20136).","DOI":"10.1109\/ICME57554.2024.10687402"},{"issue":"5","key":"10.1016\/j.ipm.2026.104865_b29","doi-asserted-by":"crossref","first-page":"2494","DOI":"10.1109\/TIP.2017.2676345","article-title":"Learning discriminative binary codes for large-scale cross-modal retrieval","volume":"26","author":"Xu","year":"2017","journal-title":"IEEE Transactions on Image Processing"},{"issue":"2","key":"10.1016\/j.ipm.2026.104865_b30","doi-asserted-by":"crossref","first-page":"851","DOI":"10.1109\/TCYB.2023.3241018","article-title":"Asymmetric supervised fusion-oriented hashing for cross-modal retrieval","volume":"54","author":"Yang","year":"2023","journal-title":"IEEE Transactions on Cybernetics"},{"key":"10.1016\/j.ipm.2026.104865_b31","doi-asserted-by":"crossref","unstructured":"Yang, E., Deng, C., Liu, W., Liu, X., Tao, D., & Gao, X. (2017). Pairwise relationship guided deep hashing for cross-modal retrieval. In Proceedings of the AAAI conference on artificial intelligence (1), (pp. 1618\u20131625).","DOI":"10.1609\/aaai.v31i1.10719"},{"issue":"3","key":"10.1016\/j.ipm.2026.104865_b32","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2023.103301","article-title":"EDMH: Efficient discrete matrix factorization hashing for multi-modal similarity retrieval","volume":"60","author":"Yang","year":"2023","journal-title":"Information Processing & Management"},{"key":"10.1016\/j.ipm.2026.104865_b33","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2023.121516","article-title":"Similarity graph-correlation reconstruction network for unsupervised cross-modal hashing","volume":"237","author":"Yao","year":"2024","journal-title":"Expert Systems with Applications"},{"key":"10.1016\/j.ipm.2026.104865_b34","first-page":"4626","article-title":"Deep graph-neighbor coherence preserving network for unsupervised cross-modal hashing","volume":"Vol. 35","author":"Yu","year":"2021"},{"issue":"6","key":"10.1016\/j.ipm.2026.104865_b35","first-page":"6475","article-title":"Weakly-supervised enhanced semantic-aware hashing for cross-modal retrieval","volume":"35","author":"Zhang","year":"2022","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"10.1016\/j.ipm.2026.104865_b36","first-page":"539","article-title":"Unsupervised generative adversarial cross-modal hashing","volume":"Vol. 32","author":"Zhang","year":"2018"},{"key":"10.1016\/j.ipm.2026.104865_b37","first-page":"387","article-title":"Unsupervised dual deep hashing with semantic-index and content-code for cross-modal retrieval","author":"Zhang","year":"2024","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"10.1016\/j.ipm.2026.104865_b38","doi-asserted-by":"crossref","unstructured":"Zhou, J., Ding, G., & Guo, Y. (2014). Latent semantic sparse hashing for cross-modal similarity search. In Proceedings of the 37th international ACM SIGIR conference on research & development in information retrieval (pp. 415\u2013424).","DOI":"10.1145\/2600428.2609610"}],"container-title":["Information Processing & Management"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0306457326002566?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0306457326002566?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T14:38:09Z","timestamp":1783694289000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0306457326002566"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,11]]},"references-count":38,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2026,11]]}},"alternative-id":["S0306457326002566"],"URL":"https:\/\/doi.org\/10.1016\/j.ipm.2026.104865","relation":{},"ISSN":["0306-4573"],"issn-type":[{"value":"0306-4573","type":"print"}],"subject":[],"published":{"date-parts":[[2026,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Hypergraph Kolmogorov\u2013Arnold networks contrastive hashing for unsupervised cross-modal retrieval","name":"articletitle","label":"Article Title"},{"value":"Information Processing & Management","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ipm.2026.104865","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"104865"}}