{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T02:00:34Z","timestamp":1792029634080,"version":"4.4.0"},"reference-count":54,"publisher":"Association for Computing Machinery (ACM)","issue":"4","funder":[{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62172166, 62276277, and 62372390"],"award-info":[{"award-number":["62172166, 62276277, and 62372390"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100021171","name":"Guangdong Basic and Applied Basic Research Foundation","doi-asserted-by":"crossref","award":["2022A1515011380, 2022B1515120059"],"award-info":[{"award-number":["2022A1515011380, 2022B1515120059"]}],"id":[{"id":"10.13039\/501100021171","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Inf. Syst."],"published-print":{"date-parts":[[2026,5,31]]},"abstract":"<jats:p>\n                    Sequential recommendation systems have become essential for personalized services in e-commerce and content platforms. While recent research has extended these systems with multi-modal features, existing approaches face three major challenges. First, they inadequately model fine-grained temporal interval distributions, failing to discriminate between high-frequency short intervals and low-frequency long intervals. Second, uniform fusion in the time domain leads to semantic misalignment across modalities because it ignores their inherent differences in the frequency domain. Third, rigid fusion strategies without self-supervised constraints lead to limited representation quality and semantic drift from pretrained embeddings. To address these issues, we propose\n                    <jats:bold>Adaptive Temporal Expert Routing with Hierarchical Wavelet Enhancement<\/jats:bold>\n                    (ATHWE) framework. ATHWE employs exponential saturation time mapping to generate temporally adaptive embeddings. These embeddings guide a sparse mixture of experts to model multi-scale user behavior dynamics. A hierarchical wavelet decomposition with band-specific gating selectively fuses complementary frequency components across modalities. Furthermore, contrastive learning and cluster-preserving objectives preserve semantic information during multi-modal fusion. Extensive experiments on multiple datasets validate the effectiveness of our framework. Our code is available at\n                    <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"https:\/\/github.com\/lulusiyuyu\/ATHWE\">https:\/\/github.com\/lulusiyuyu\/ATHWE<\/jats:ext-link>\n                    .\n                  <\/jats:p>","DOI":"10.1145\/3801160","type":"journal-article","created":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T13:23:19Z","timestamp":1773062599000},"page":"1-27","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Adaptive Temporal Expert Routing with Hierarchical Wavelet Enhancement for Multi-Modal Sequential Recommendation"],"prefix":"10.1145","volume":"44","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-4693-0683","authenticated-orcid":false,"given":"Shiyu","family":"Liu","sequence":"first","affiliation":[{"name":"School of Computer Science, South China Normal University, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-6497-4317","authenticated-orcid":false,"given":"Jinzhao","family":"Su","sequence":"additional","affiliation":[{"name":"School of Computer Science, South China Normal University, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5972-559X","authenticated-orcid":false,"given":"Chang-Dong","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Sun Yat-Sen University, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9573-0780","authenticated-orcid":false,"given":"Shengli","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Software and Microelectronics, Peking University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2275-997X","authenticated-orcid":false,"given":"Chen","family":"Lin","sequence":"additional","affiliation":[{"name":"School of Informatics, Xiamen University, Xiamen, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8659-4062","authenticated-orcid":false,"given":"Zhenhua","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Computer Science, South China Normal University, Guangzhou, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,5,11]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/S0042-6989(97)00121-1"},{"key":"e_1_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1145\/3583780.3614978"},{"key":"e_1_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1145\/3159652.3159668"},{"key":"e_1_3_1_5_2","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3512090"},{"key":"e_1_3_1_6_2","doi-asserted-by":"publisher","DOI":"10.1002\/cpa.3160410705"},{"key":"e_1_3_1_7_2","first-page":"4171","volume-title":"Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies","volume":"1","author":"Devlin Jacob","year":"2019","unstructured":"Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019. Bert: Pre-training of deep bidirectional transformers for language understanding. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Vol. 1, 4171\u20134186."},{"key":"e_1_3_1_8_2","volume-title":"Proceedings of the 9th International Conference on Learning Representations (ICLR \u201921)","author":"Dosovitskiy Alexey","year":"2021","unstructured":"Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al. 2021. An image is worth 16x16 words: Transformers for image recognition at scale. In Proceedings of the 9th International Conference on Learning Representations (ICLR \u201921)."},{"key":"e_1_3_1_9_2","doi-asserted-by":"publisher","DOI":"10.1145\/3539618.3591689"},{"key":"e_1_3_1_10_2","doi-asserted-by":"publisher","DOI":"10.1145\/3426723"},{"key":"e_1_3_1_11_2","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2023.3317175"},{"key":"e_1_3_1_12_2","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2025.3543377"},{"key":"e_1_3_1_13_2","first-page":"1","volume-title":"Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP \u201925)","author":"Guo Xu","year":"2025","unstructured":"Xu Guo, Tong Zhang, Yufei Xue, Chenxu Wang, Fuyun Wang, and Zhen Cui. 2025. \\(M^{3}\\) Rec: Selective state space models with mixture-of-modality experts for multi-modal sequential recommendation. In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP \u201925). IEEE, 1\u20135."},{"key":"e_1_3_1_14_2","unstructured":"Bal\u00e1zs Hidasi Alexandros Karatzoglou Linas Baltrunas and Domonkos Tikk. 2015. Session-based recommendations with recurrent neural networks. arXiv:1511.06939. Retrieved from https:\/\/arxiv.org\/abs\/1511.06939"},{"key":"e_1_3_1_15_2","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539381"},{"key":"e_1_3_1_16_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-023-09328-9"},{"key":"e_1_3_1_17_2","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2021.3131349"},{"key":"e_1_3_1_18_2","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2019.2955567"},{"key":"e_1_3_1_19_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00371-025-04006-4"},{"key":"e_1_3_1_20_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2018.00035"},{"key":"e_1_3_1_21_2","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2009.263"},{"key":"e_1_3_1_22_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-96-8180-8_22"},{"key":"e_1_3_1_23_2","doi-asserted-by":"publisher","DOI":"10.1145\/3336191.3371786"},{"key":"e_1_3_1_24_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2025.107906"},{"key":"e_1_3_1_25_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2024.106382"},{"key":"e_1_3_1_26_2","doi-asserted-by":"publisher","DOI":"10.1145\/3717833"},{"key":"e_1_3_1_27_2","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403091"},{"key":"e_1_3_1_28_2","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2024.3475809"},{"key":"e_1_3_1_29_2","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3053245"},{"key":"e_1_3_1_30_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCSS.2024.3411043"},{"key":"e_1_3_1_31_2","doi-asserted-by":"publisher","DOI":"10.1145\/3109859.3109896"},{"key":"e_1_3_1_32_2","doi-asserted-by":"publisher","DOI":"10.1145\/1772690.1772773"},{"key":"e_1_3_1_33_2","first-page":"1","volume-title":"IEEE Transactions on Computational Social Systems","author":"Su Jinzhao","year":"2025","unstructured":"Jinzhao Su, Zhenhua Huang, Chang-Dong Wang, and Yunwen Chen. 2025. MLSA4Rec: Mamba combined with low-rank decomposed self-attention for sequential recommendation. IEEE Transactions on Computational Social Systems, (2025) 1\u201317. 10.1109\/TCSS.2025.3623273"},{"key":"e_1_3_1_34_2","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3357895"},{"key":"e_1_3_1_35_2","first-page":"1","volume-title":"IEEE Transactions on Geoscience and Remote Sensing","volume":"62","author":"Tao Hailin","year":"2023","unstructured":"Hailin Tao, Jinjiang Li, Zhen Hua, and Fan Zhang. 2023. DUDB: Deep unfolding-based dual-branch feature fusion network for pan-sharpening remote sensing images. IEEE Transactions on Geoscience and Remote Sensing 62 (2023), 1\u201317."},{"key":"e_1_3_1_36_2","first-page":"5998","volume-title":"Advances in Neural Information Processing Systems","volume":"30","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, \u0141ukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. Advances in Neural Information Processing Systems, Vol. 30, 5998\u20136008."},{"key":"e_1_3_1_37_2","doi-asserted-by":"publisher","DOI":"10.1145\/3522673"},{"key":"e_1_3_1_38_2","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219869"},{"key":"e_1_3_1_39_2","doi-asserted-by":"publisher","DOI":"10.1145\/3581783.3611967"},{"key":"e_1_3_1_40_2","doi-asserted-by":"publisher","DOI":"10.1145\/3726302.3730087"},{"key":"e_1_3_1_41_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2025.108593"},{"key":"e_1_3_1_42_2","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3351034"},{"key":"e_1_3_1_43_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2024.112257"},{"key":"e_1_3_1_44_2","doi-asserted-by":"publisher","DOI":"10.1145\/3627673.3680037"},{"key":"e_1_3_1_45_2","doi-asserted-by":"publisher","DOI":"10.1145\/2911451.2914683"},{"key":"e_1_3_1_46_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10844-024-00887-4"},{"key":"e_1_3_1_47_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2023.3278131"},{"key":"e_1_3_1_48_2","doi-asserted-by":"publisher","DOI":"10.1007\/s41095-023-0369-x"},{"key":"e_1_3_1_49_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i8.28786"},{"key":"e_1_3_1_50_2","doi-asserted-by":"publisher","DOI":"10.1145\/3696410.3714676"},{"key":"e_1_3_1_51_2","first-page":"1","article-title":"SSD4Rec: A structured state space duality model for efficient sequential recommendation","author":"Zhang Yifeng","year":"2025","unstructured":"Yifeng Zhang, Haohao Qu, Liangbo Ning, Wenqi Fan, and Qing Li. 2025. SSD4Rec: A structured state space duality model for efficient sequential recommendation. ACM Transactions on Information Systems 29 (2025), 1\u201326.","journal-title":"ACM Transactions on Information Systems"},{"key":"e_1_3_1_52_2","doi-asserted-by":"publisher","DOI":"10.1145\/3665325"},{"key":"e_1_3_1_53_2","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3411954"},{"key":"e_1_3_1_54_2","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3512111"},{"key":"e_1_3_1_55_2","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2024.3377243"}],"container-title":["ACM Transactions on Information Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3801160","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,16]],"date-time":"2026-05-16T15:45:23Z","timestamp":1778946323000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3801160"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5,11]]},"references-count":54,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2026,5,31]]}},"alternative-id":["10.1145\/3801160"],"URL":"https:\/\/doi.org\/10.1145\/3801160","relation":{},"ISSN":["1046-8188","1558-2868"],"issn-type":[{"value":"1046-8188","type":"print"},{"value":"1558-2868","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,5,11]]},"assertion":[{"value":"2025-11-14","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-02-27","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-05-11","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}