{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T11:08:12Z","timestamp":1783940892027,"version":"3.55.0"},"reference-count":49,"publisher":"Springer Science and Business Media LLC","issue":"8","license":[{"start":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T00:00:00Z","timestamp":1783900800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T00:00:00Z","timestamp":1783900800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Youth Project of Humanities and Social Sciences of the Ministry of Education of China","award":["No. 25YJC860021"],"award-info":[{"award-number":["No. 25YJC860021"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Computing"],"published-print":{"date-parts":[[2026,8]]},"DOI":"10.1007\/s00607-026-01716-y","type":"journal-article","created":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T10:54:23Z","timestamp":1783940063000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A multimodal sequential recommendation method integrating time-conditioned modality importance modeling and adversarial debiasing"],"prefix":"10.1007","volume":"108","author":[{"given":"Weiwei","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chengshan","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenjie","family":"Geng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,13]]},"reference":[{"key":"1716_CR1","doi-asserted-by":"crossref","unstructured":"He R, McAuley J (2016) Fusing similarity models with markov chains for sparse sequential recommendation. In: 2016 IEEE 16th International Conference on Data Mining (ICDM), pp. 191\u2013200","DOI":"10.1109\/ICDM.2016.0030"},{"key":"1716_CR2","doi-asserted-by":"crossref","unstructured":"Rendle S, Freudenthaler C, Schmidt-Thieme L (2010) Factorizing personalized markov chains for next-basket recommendation. Proceedings of the 19th International Conference on World Wide Web. pp 811\u2013820","DOI":"10.1145\/1772690.1772773"},{"key":"1716_CR3","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.110078","volume":"259","author":"N Zhao","year":"2023","unstructured":"Zhao N, Long Z, Wang J, Zhao Z-D (2023) AGRE: A knowledge graph recommendation algorithm based on multiple paths embeddings rnn encoder. Knowl-Based Syst 259:110078","journal-title":"Knowl-Based Syst"},{"key":"1716_CR4","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.116595","volume":"195","author":"M Chen","year":"2022","unstructured":"Chen M, Ma T, Zhou X (2022) CoCNN: Co-occurrence cnn for recommendation. Expert Syst Appl 195:116595. https:\/\/doi.org\/10.1016\/j.eswa.2022.116595","journal-title":"Expert Syst Appl"},{"key":"1716_CR5","doi-asserted-by":"publisher","unstructured":"Kang WC, McAuley J (2018) Self-attentive sequential recommendation. In: 2018 IEEE International Conference on Data Mining (ICDM), pp. 197\u2013206. https:\/\/doi.org\/10.1109\/ICDM.2018.00035","DOI":"10.1109\/ICDM.2018.00035"},{"key":"1716_CR6","doi-asserted-by":"publisher","unstructured":"Wu S, Tang Y, Zhu Y, Wang L, Xie X, Tan T (2019) Session-based recommendation with graph neural networks. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 33, pp. 346\u2013353. https:\/\/doi.org\/10.1609\/aaai.v33i01.3301346","DOI":"10.1609\/aaai.v33i01.3301346"},{"issue":"6","key":"1716_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3670995","volume":"42","author":"Y Jiang","year":"2024","unstructured":"Jiang Y, Xu Y, Yang Y, Yang F, Wang P, Li C, Zhuang F, Xiong H (2024) TriMLP: A foundational mlp-like architecture for sequential recommendation. ACM Trans Inf Syst 42(6):1\u201334","journal-title":"ACM Trans Inf Syst"},{"key":"1716_CR8","doi-asserted-by":"crossref","unstructured":"Li M, Zhang Z, Zhao X, Wang W, Zhao M, Wu R, Guo R (2023) Automlp: Automated mlp for sequential recommendations. In: Proceedings of the ACM Web Conference 2023, pp. 1190\u20131198","DOI":"10.1145\/3543507.3583440"},{"key":"1716_CR9","doi-asserted-by":"crossref","unstructured":"Ye Y, Guo W, Chin JY, Wang H, Zhu H, Lin X, Ye Y, Liu Y, Tang R, Lian D, et al (2025) Fuxi-$$\\alpha $$: Scaling recommendation model with feature interaction enhanced transformer. In: Companion Proceedings of the ACM on Web Conference 2025, pp. 557\u2013566","DOI":"10.1145\/3701716.3715448"},{"key":"1716_CR10","doi-asserted-by":"crossref","unstructured":"Qiu R, Huang Z, Yin H, Wang Z (2022) Contrastive learning for representation degeneration problem in sequential recommendation. Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining. pp 813\u2013823","DOI":"10.1145\/3488560.3498433"},{"key":"1716_CR11","doi-asserted-by":"crossref","unstructured":"Bian S, Pan X, Zhao WX, Wang J, Wang C, Wen JR (2023) Multi-modal mixture of experts represetation learning for sequential recommendation. In: Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, pp. 110\u2013119","DOI":"10.1145\/3583780.3614978"},{"key":"1716_CR12","doi-asserted-by":"crossref","unstructured":"Guo X, Zhang T, Xue Y, Wang C, Wang F, Cui Z (2025) M3rec: Selective state space models with mixture-of-modality experts for multi-modal sequential recommendation. In: ICASSP 2025-2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1\u20135","DOI":"10.1109\/ICASSP49660.2025.10887582"},{"key":"1716_CR13","doi-asserted-by":"crossref","unstructured":"Hu H, Guo W, Liu Y, Kan M-Y (2023) Adaptive multi-modalities fusion in sequential recommendation systems. Proceedings of the 32nd ACM International Conference on Information and Knowledge Management. pp 843\u2013853","DOI":"10.1145\/3583780.3614775"},{"key":"1716_CR14","doi-asserted-by":"crossref","unstructured":"Liang J, Zhao X, Li M, Zhang Z, Wang W, Liu H, Liu Z (2023) Mmmlp: Multi-modal multilayer perceptron for sequential recommendations. In: Proceedings of the ACM Web Conference 2023, pp. 1109\u20131117","DOI":"10.1145\/3543507.3583378"},{"key":"1716_CR15","doi-asserted-by":"publisher","first-page":"3672","DOI":"10.1145\/3696410.3714676","volume":"2025","author":"S Zhang","year":"2025","unstructured":"Zhang S, Chen L, Shen D, Wang C, Xiong H (2025) Hierarchical time-aware mixture of experts for multi-modal sequential recommendation. Proc ACM Web Conf 2025:3672\u20133682. https:\/\/doi.org\/10.1145\/3696410.3714676","journal-title":"Proc ACM Web Conf"},{"issue":"2","key":"1716_CR16","doi-asserted-by":"publisher","first-page":"317","DOI":"10.1109\/TKDE.2018.2881260","volume":"32","author":"Q Cui","year":"2018","unstructured":"Cui Q, Wu S, Liu Q, Zhong W, Wang L (2018) MV-RNN: A multi-view recurrent neural network for sequential recommendation. IEEE Trans Knowl Data Eng 32(2):317\u2013331","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"1716_CR17","doi-asserted-by":"crossref","unstructured":"Wang J, Zeng Z, Wang Y, Wang Y, Lu X, Li T, Yuan J, Zhang R, Zheng HT, Xia ST (2023) Missrec: Pre-training and transferring multi-modal interest-aware sequence representation for recommendation. In: Proceedings of the 31st ACM International Conference on Multimedia, pp. 6548\u20136557","DOI":"10.1145\/3581783.3611967"},{"key":"1716_CR18","unstructured":"Hong M-Y, Hsu Y-J, Chiang M-C, Lin C (2025) MTSTRec: Multimodal time-aligned shared token recommender. Proceedings of the 42nd International Conference on Machine Learning. pp 23640\u201323661"},{"key":"1716_CR19","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2024.124667","volume":"255","author":"Q Zhao","year":"2024","unstructured":"Zhao Q, Chen X, Zhang H, Li X (2024) Dynamic hierarchical attention network for news recommendation. Expert Syst Appl 255:124667. https:\/\/doi.org\/10.1016\/j.eswa.2024.124667","journal-title":"Expert Syst Appl"},{"key":"1716_CR20","doi-asserted-by":"crossref","unstructured":"Liu R, Peng H, Chen Y, Zhang D (2020) HyperNews: Simultaneous news recommendation and active-time prediction via a double-task deep neural network. In IJCAI 20:3487\u20133493","DOI":"10.24963\/ijcai.2020\/482"},{"key":"1716_CR21","doi-asserted-by":"publisher","unstructured":"Li J, Wang Y, McAuley J (2020) Time interval aware self-attention for sequential recommendation. In: Proceedings of the 13th International Conference on Web Search and Data Mining, pp. 322\u2013330. https:\/\/doi.org\/10.1145\/3336191.3371786","DOI":"10.1145\/3336191.3371786"},{"key":"1716_CR22","doi-asserted-by":"crossref","unstructured":"Xu L, Tian Z, Li B, Zhang J, Wang D, Wang H, Wang J, Chen S, Zhao WX (2024) Sequence-level semantic representation fusion for recommender systems. In: Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, pp. 5015\u20135022","DOI":"10.1145\/3627673.3680037"},{"key":"1716_CR23","doi-asserted-by":"publisher","unstructured":"Hidasi B, Karatzoglou A, Baltrunas L, Tikk D (2015) Session-based recommendations with recurrent neural networks. arXiv preprint arXiv:1511.06939https:\/\/doi.org\/10.48550\/arXiv.1511.06939","DOI":"10.48550\/arXiv.1511.06939"},{"key":"1716_CR24","doi-asserted-by":"publisher","unstructured":"Tang J, Wang K (2018) Personalized top-n sequential recommendation via convolutional sequence embedding. In: Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining, pp. 565\u2013573. https:\/\/doi.org\/10.1145\/3159652.3159656","DOI":"10.1145\/3159652.3159656"},{"key":"1716_CR25","doi-asserted-by":"publisher","unstructured":"Sun F, Liu J, Wu J, Pei C, Lin X, Ou W, Jiang P (2019) BERT4Rec: Sequential recommendation with bidirectional encoder representations from transformer. In: Proceedings of the 28th ACM International Conference on Information and Knowledge Management, pp. 1441\u20131450 https:\/\/doi.org\/10.1145\/3357384.3357895","DOI":"10.1145\/3357384.3357895"},{"key":"1716_CR26","doi-asserted-by":"crossref","unstructured":"Liu C, Li X, Cai G, Dong Z, Zhu H, Shang L (2021) Noninvasive self-attention for side information fusion in sequential recommendation. Proceedings of the AAAI Conference on Artificial Intelligence, vol 35. pp 4249\u20134256","DOI":"10.1609\/aaai.v35i5.16549"},{"key":"1716_CR27","doi-asserted-by":"crossref","unstructured":"Xie Y, Zhou P, Kim S (2022) Decoupled side information fusion for sequential recommendation. Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval. pp 1611\u20131621","DOI":"10.1145\/3477495.3531963"},{"key":"1716_CR28","doi-asserted-by":"crossref","unstructured":"Fu J, Ge X, Xin X, Karatzoglou A, Arapakis I, Wang J, Jose JM (2024) IISAN: Efficiently adapting multimodal representation for sequential recommendation with decoupled PEFT. Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval. pp 687\u2013697","DOI":"10.1145\/3626772.3657725"},{"key":"1716_CR29","doi-asserted-by":"crossref","unstructured":"Ye Y, Zheng Z, Shen Y, Wang T, Zhang H, Zhu P, Yu R, Zhang K, Xiong H (2025) Harnessing multimodal large language models for multimodal sequential recommendation. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 39, pp. 13069\u201313077","DOI":"10.1609\/aaai.v39i12.33426"},{"issue":"6","key":"1716_CR30","first-page":"16","volume":"31","author":"C Xiaopeng","year":"2024","unstructured":"Xiaopeng C, Linying Z, Qiuxian C, Hailong N, Yizhuo D (2024) A cross-modal fusion network based on graph feature learning for multimodal emotion recognition. The Journal of China Universities of Posts and Telecommunications 31(6):16","journal-title":"The Journal of China Universities of Posts and Telecommunications"},{"issue":"2","key":"1716_CR31","doi-asserted-by":"publisher","first-page":"3288","DOI":"10.1109\/TNNLS.2024.3359275","volume":"36","author":"Z Wu","year":"2024","unstructured":"Wu Z, Cao L, Qi L (2024) evae: Evolutionary variational autoencoder. IEEE Trans Neural Networks Learn Syst 36(2):3288\u20133299","journal-title":"IEEE Trans Neural Networks Learn Syst"},{"key":"1716_CR32","doi-asserted-by":"crossref","unstructured":"Wu Z, Fan X, Li J, Zhao Z, Chen H, Cao L (2025) Sepdiff: Self-encoding parameter diffusion for learning latent semantics. In: Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V. 2, pp. 3273\u20133284","DOI":"10.1145\/3711896.3737125"},{"key":"1716_CR33","doi-asserted-by":"crossref","unstructured":"Cho SM, Park E, Yoo S (2020) MEANTIME: Mixture of attention mechanisms with multi-temporal embeddings for sequential recommendation. Proceedings of the 14th ACM Conference on Recommender Systems. pp 515\u2013520","DOI":"10.1145\/3383313.3412216"},{"key":"1716_CR34","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2022.109894","volume":"133","author":"Y Zhang","year":"2023","unstructured":"Zhang Y, Yang B, Liu H, Li D (2023) A time-aware self-attention based neural network model for sequential recommendation. Appl Soft Comput 133:109894. https:\/\/doi.org\/10.1016\/j.asoc.2022.109894","journal-title":"Appl Soft Comput"},{"issue":"6","key":"1716_CR35","doi-asserted-by":"publisher","first-page":"2686","DOI":"10.1109\/TKDE.2023.3324312","volume":"36","author":"Y Dang","year":"2023","unstructured":"Dang Y, Yang E, Guo G, Jiang L, Wang X, Xu X, Sun Q, Liu H (2023) TiCoSeRec: Augmenting data to uniform sequences by time intervals for effective recommendation. IEEE Trans Knowl Data Eng 36(6):2686\u20132700","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"1716_CR36","doi-asserted-by":"publisher","unstructured":"Jung H, Seo H, Lim C (2024) Sequential recommendation on temporal proximities with contrastive learning and self-attention. arXiv preprint arXiv:2402.09784https:\/\/doi.org\/10.48550\/arXiv.2402.09784","DOI":"10.48550\/arXiv.2402.09784"},{"key":"1716_CR37","unstructured":"Wu Z, Cao L, Zhang Q, Zhou J, Chen H (2024) Weakly augmented variational autoencoder in time series anomaly detection.arXiv:2401.03341 arXiv preprint"},{"key":"1716_CR38","doi-asserted-by":"publisher","unstructured":"Devlin J, Chang M-W, Lee K, Toutanova K (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, Volume 1 (long and Short Papers), pp. 4171\u20134186. https:\/\/doi.org\/10.18653\/v1\/N19-1423","DOI":"10.18653\/v1\/N19-1423"},{"key":"1716_CR39","doi-asserted-by":"publisher","unstructured":"Dosovitskiy A, Beyer L, Kolesnikov A, Weissenborn D, Zhai X, Unterthiner T, Dehghani M, Minderer M, Heigold G, Gelly S, et al (2020) An image is worth 16x16 words: Transformers for image recognition at scale. arXiv preprint arXiv:2010.11929, https:\/\/doi.org\/10.48550\/arXiv.2010.11929","DOI":"10.48550\/arXiv.2010.11929"},{"key":"1716_CR40","doi-asserted-by":"crossref","unstructured":"Wang C, Zhu H, Hao Q, Xiao K, Xiong H (2021) Variable interval time sequence modeling for career trajectory prediction: Deep collaborative perspective. Proceedings of the Web Conference 2021. pp 612\u2013623","DOI":"10.1145\/3442381.3449959"},{"key":"1716_CR41","doi-asserted-by":"crossref","unstructured":"Ye W, Wang S, Chen X, Wang X, Qin Z, Yin D (2020) Time matters: Sequential recommendation with complex temporal information. In: Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 1459\u20131468","DOI":"10.1145\/3397271.3401154"},{"issue":"3","key":"1716_CR42","doi-asserted-by":"publisher","first-page":"583","DOI":"10.1007\/s11257-023-09367-w","volume":"34","author":"J Sun","year":"2024","unstructured":"Sun J, Du S, Liang R, Shen X, Li Q, Liu S, Yang Z (2024) Deep adversarial group recommendation with user feature space separation. User Model User-Adap Inter 34(3):583\u2013615. https:\/\/doi.org\/10.1007\/s11257-023-09367-w","journal-title":"User Model User-Adap Inter"},{"key":"1716_CR43","doi-asserted-by":"crossref","unstructured":"Yue Z, Wang Y, He Z, Zeng H, McAuley J, Wang D (2024) Linear recurrent units for sequential recommendation. In: Proceedings of the 17th ACM International Conference on Web Search and Data Mining, pp. 930\u2013938","DOI":"10.1145\/3616855.3635760"},{"key":"1716_CR44","doi-asserted-by":"crossref","unstructured":"Du X, Yuan H, Zhao P, Qu J, Zhuang F, Liu G, Liu Y, Sheng VS (2023) Frequency enhanced hybrid attention network for sequential recommendation. In: Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 78\u201388","DOI":"10.1145\/3539618.3591689"},{"key":"1716_CR45","doi-asserted-by":"crossref","unstructured":"Lee S, Yeo K, Kim E, Kim J, Kim C, Jeon Y, Kim J, Lee J (2025) Mixture of conditional attention for multimodal fusion in sequential recommendation. In: Pacific-Asia Conference on Knowledge Discovery and Data Mining, pp. 278\u2013290","DOI":"10.1007\/978-981-96-8180-8_22"},{"key":"1716_CR46","doi-asserted-by":"crossref","unstructured":"Wang M, Xiao Y, Wang B, et al (2025) FindRec: Stein-guided entropic flow for multi-modal sequential recommendation. In: Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V. 2, pp. 3008\u20133018","DOI":"10.1145\/3711896.3736968"},{"key":"1716_CR47","doi-asserted-by":"crossref","unstructured":"Li Z, Zhu J, Huang C (2026) Capturing dynamic user interests under modality imbalance for multimodal sequential recommendation. Proceedings of the AAAI Conference on Artificial Intelligence, vol 40. pp 15198\u201315206","DOI":"10.1609\/aaai.v40i18.38544"},{"key":"1716_CR48","doi-asserted-by":"crossref","unstructured":"Zhao WX, Mu S, Hou Y, Lin Z, Chen Y, Pan X, Li K, Lu Y, Wang H, Tian C, et al (2021) Recbole: Towards a unified, comprehensive and efficient framework for recommendation algorithms. In: Proceedings of the 30th Acm International Conference on Information & Knowledge Management, pp. 4653\u20134664","DOI":"10.1145\/3459637.3482016"},{"key":"1716_CR49","doi-asserted-by":"publisher","unstructured":"Kingma DP, Ba J (2014) Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980, https:\/\/doi.org\/10.48550\/arXiv.1412.6980","DOI":"10.48550\/arXiv.1412.6980"}],"container-title":["Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00607-026-01716-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00607-026-01716-y","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00607-026-01716-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T10:54:30Z","timestamp":1783940070000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00607-026-01716-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,13]]},"references-count":49,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2026,8]]}},"alternative-id":["1716"],"URL":"https:\/\/doi.org\/10.1007\/s00607-026-01716-y","relation":{},"ISSN":["0010-485X","1436-5057"],"issn-type":[{"value":"0010-485X","type":"print"},{"value":"1436-5057","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,13]]},"assertion":[{"value":"22 May 2026","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 July 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 July 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval and consent to participate"}},{"value":"Not applicable.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}}],"article-number":"120"}}