{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T20:42:28Z","timestamp":1785530548917,"version":"3.56.0"},"reference-count":62,"publisher":"Association for Computing Machinery (ACM)","issue":"3","license":[{"start":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T00:00:00Z","timestamp":1743120000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Natural Science Foundation of Shandong, China","award":["ZR2024MF119"],"award-info":[{"award-number":["ZR2024MF119"]}]},{"name":"Singapore MOE AcRF Tier-2","award":["MOE-T2EP20223-0004"],"award-info":[{"award-number":["MOE-T2EP20223-0004"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62172263 and 62176144"],"award-info":[{"award-number":["62172263 and 62176144"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Major Fundamental Research Project of Shandong, China","award":["ZR2019ZD03"],"award-info":[{"award-number":["ZR2019ZD03"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Inf. Syst."],"published-print":{"date-parts":[[2025,5,31]]},"abstract":"<jats:p>\n            Providing sequential recommendations along with easily comprehensible natural language explanations can significantly enhance users\u2019 trust in the recommender systems. However, this approach presents two key challenges: (1) The different objectives of the two tasks make it challenging to achieve joint optimization and mutual enhancement. (2) The simultaneous generation of accurate sequential recommendations and high-quality natural language explanations presents serious challenges to the model\u2019s time and space efficiency. To address these challenges, we propose a general and efficient multi-task self-prompt framework for explainable sequential recommendation (ARTS), which improves collaboration performance and time and space efficiency of multi-task modules based on the generated personalized semantic prompts. Specifically, we propose a self-prompt generator that transfers the user\u2019s global behavior features into the continuous prompt, achieving efficient information sharing among multi-task modules. Additionally, we design a personalized prompt-based short sequence inputs strategy under the pre-training and prompt-tuning paradigm, which achieves mutual enhancement among the multi-task modules and significantly improves the model\u2019s time and space efficiency. Extensive experiments have verified that the proposed ARTS outperforms the state-of-the-art methods in both sequential recommendation and explanation generation tasks. The generality, efficiency and effectiveness of each module of the framework have also been validated through various experiments\n            <jats:xref ref-type=\"fn\">\n              <jats:sup>1<\/jats:sup>\n            <\/jats:xref>\n            .\n          <\/jats:p>","DOI":"10.1145\/3717833","type":"journal-article","created":{"date-parts":[[2025,2,14]],"date-time":"2025-02-14T15:06:56Z","timestamp":1739545616000},"page":"1-30","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["ARTS: A General and Efficient Multi-Task Self-Prompt Framework for Explainable Sequential Recommendation"],"prefix":"10.1145","volume":"43","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-1685-8099","authenticated-orcid":false,"given":"Zunlong","family":"Liu","sequence":"first","affiliation":[{"name":"Shandong Normal University, Jinan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4979-0608","authenticated-orcid":false,"given":"Yang","family":"Xu","sequence":"additional","affiliation":[{"name":"Shandong Normal University, Jinan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4430-6373","authenticated-orcid":false,"given":"Gao","family":"Cong","sequence":"additional","affiliation":[{"name":"School of Computing, Nanyang Technological University, Singapore, Singapore"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2993-7142","authenticated-orcid":false,"given":"Lei","family":"Zhu","sequence":"additional","affiliation":[{"name":"Tongji University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9850-3751","authenticated-orcid":false,"given":"Qinjun","family":"Qiu","sequence":"additional","affiliation":[{"name":"School of Computer Science, China University of Geosciences, Wuhan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-7777-7292","authenticated-orcid":false,"given":"Huaxiang","family":"Zhang","sequence":"additional","affiliation":[{"name":"Shandong Normal University, Jinan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2025,3,28]]},"reference":[{"key":"e_1_3_2_2_2","unstructured":"Yihan Cao Siyu Li Yixin Liu Zhiling Yan Yutong Dai Philip S. 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Retrieved from https:\/\/arxiv.org\/abs\/2010.11929"},{"key":"e_1_3_2_7_2","first-page":"1","volume-title":"Proceedings of the ACM Transactions on Information Systems","author":"Guo Lei","year":"2023","unstructured":"Lei Guo, Hao Liu, Lei Zhu, Weili Guan, and Zhiyong Cheng. 2023. DA-DAN: A dual adversarial domain adaption network for unsupervised non-overlapping cross-domain recommendation. In Proceedings of the ACM Transactions on Information Systems, 1\u201327."},{"key":"e_1_3_2_8_2","first-page":"770","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","author":"He Kaiming","year":"2016","unstructured":"Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016. Deep residual learning for image recognition. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 770\u2013778."},{"key":"e_1_3_2_9_2","unstructured":"Bal\u00e1zs Hidasi Alexandros Karatzoglou Linas Baltrunas and Domonkos Tikk. 2016. 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Retrieved from https:\/\/aclanthology.org\/2024.findings-emnlp.22.pdf","DOI":"10.18653\/v1\/2024.findings-emnlp.22"},{"key":"e_1_3_2_27_2","first-page":"1","volume-title":"Proceedings of the Advances in Neural Information Processing Systems","author":"Mikolov Tomas","year":"2013","unstructured":"Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean. 2013. Distributed representations of words and phrases and their compositionality. In Proceedings of the Advances in Neural Information Processing Systems, 1\u20139."},{"key":"e_1_3_2_28_2","first-page":"188","volume-title":"Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing","author":"Ni Jianmo","year":"2019","unstructured":"Jianmo Ni, Jiacheng Li, and Julian McAuley. 2019. Justifying recommendations using distantly-labeled reviews and fine-grained aspects. 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Retrieved from https:\/\/aclanthology.org\/D19-1250.pdf"},{"key":"e_1_3_2_30_2","first-page":"579","volume-title":"Proceedings of the 28th ACM International Conference on Information and Knowledge Management","author":"Qiu Ruihong","year":"2019","unstructured":"Ruihong Qiu, Jingjing Li, Zi Huang, and Hongzhi Yin. 2019. Rethinking the item order in session-based recommendation with graph neural networks. In Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 579\u2013588."},{"key":"e_1_3_2_31_2","first-page":"8748","volume-title":"Proceedings of the International Conference on Machine Learning","author":"Radford Alec","year":"2021","unstructured":"Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al. 2021. Learning transferable visual models from natural language supervision. 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Retrieved from https:\/\/arxiv.org\/abs\/2308.09568"},{"issue":"7","key":"e_1_3_2_46_2","doi-asserted-by":"crossref","first-page":"3376","DOI":"10.1109\/TKDE.2024.3357498","article-title":"Personalized prompt for sequential recommendation","volume":"36","author":"Wu Yiqing","year":"2024","unstructured":"Yiqing Wu, Ruobing Xie, Yongchun Zhu, Fuzhen Zhuang, Xu Zhang, Leyu Lin, and Qing He. 2024. Personalized prompt for sequential recommendation. IEEE Transactions on Knowledge and Data Engineering 36, 7 (2024), 3376\u20133389.","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"issue":"7","key":"e_1_3_2_47_2","doi-asserted-by":"crossref","first-page":"3376","DOI":"10.1109\/TKDE.2024.3357498","article-title":"Personalized prompt for sequential recommendation","volume":"36","author":"Wu Yiqing","year":"2024","unstructured":"Yiqing Wu, Ruobing Xie, Yongchun Zhu, Fuzhen Zhuang, Xu Zhang, Leyu Lin, and Qing He. 2024. Personalized prompt for sequential recommendation. 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In Proceedings of the IEEE 38th International Conference on Data Engineering, 1259\u20131273."},{"key":"e_1_3_2_50_2","first-page":"3940","volume-title":"Proceedings of the International Joint Conference on Artificial Intelligence","author":"Xu Chengfeng","year":"2019","unstructured":"Chengfeng Xu, Pengpeng Zhao, Yanchi Liu, Victor S Sheng, Jiajie Xu, Fuzhen Zhuang, Junhua Fang, and Xiaofang Zhou. 2019. Graph contextualized self-attention network for session-based recommendation. In Proceedings of the International Joint Conference on Artificial Intelligence, 3940\u20133946."},{"issue":"1","key":"e_1_3_2_51_2","first-page":"741","article-title":"Multi-modal discrete collaborative filtering for efficient cold-start recommendation","volume":"35","author":"Xu Yang","year":"2021","unstructured":"Yang Xu, Lei Zhu, Zhiyong Cheng, Jingjing Li, Zheng Zhang, and Huaxiang Zhang. 2021. Multi-modal discrete collaborative filtering for efficient cold-start recommendation. IEEE Transactions on Knowledge and Data Engineering 35, 1 (2021), 741\u2013755.","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"e_1_3_2_52_2","unstructured":"Wojciech Zaremba Ilya Sutskever and Oriol Vinyals. 2014. Recurrent neural network regularization. arXiv:1409.2329. Retrieved from https:\/\/arxiv.org\/abs\/1409.2329"},{"key":"e_1_3_2_53_2","unstructured":"Susan Zhang Stephen Roller Naman Goyal Mikel Artetxe Moya Chen Shuohui Chen Christopher Dewan Mona Diab Xian Li and Xi Victoria Lin. 2022. Opt: Open pre-trained transformer language models. arXiv:2205.01068. Retrieved from https:\/\/arxiv.org\/abs\/2205.01068"},{"key":"e_1_3_2_54_2","first-page":"83","volume-title":"Proceedings of the 37th International ACM SIGIR Conference on Research & Development in Information Retrieval","author":"Zhang Yongfeng","year":"2014","unstructured":"Yongfeng Zhang, Guokun Lai, Min Zhang, Yi Zhang, Yiqun Liu, and Shaoping Ma. 2014. Explicit factor models for explainable recommendation based on phrase-level sentiment analysis. In Proceedings of the 37th International ACM SIGIR Conference on Research & Development in Information Retrieval, 83\u201392."},{"issue":"3","key":"e_1_3_2_55_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3631521","article-title":"Triple dual learning for opinion-based explainable recommendation","volume":"42","author":"Zhang Yuting","year":"2023","unstructured":"Yuting Zhang, Ying Sun, Fuzhen Zhuang, Yongchun Zhu, Zhulin An, and Yongjun Xu. 2023. Triple dual learning for opinion-based explainable recommendation. ACM Transactions on Information Systems 42, 3 (2023), 1\u201327.","journal-title":"ACM Transactions on Information Systems"},{"key":"e_1_3_2_56_2","unstructured":"Yabin Zhang Wenhui Yu Erhan Zhang Xu Chen Lantao Hu Peng Jiang and Kun Gai. 2024. RecGPT: Generative personalized prompts for sequential recommendation via ChatGPT training paradigm. arXiv:2404.08675. Retrieved from https:\/\/arxiv.org\/abs\/2404.08675"},{"key":"e_1_3_2_57_2","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1145\/3539618.3591752","volume-title":"Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval","author":"Zhang Zizhuo","year":"2023","unstructured":"Zizhuo Zhang and Bang Wang. 2023. Prompt learning for news recommendation. In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 227\u2013237."},{"key":"e_1_3_2_58_2","unstructured":"Wayne Xin Zhao Kun Zhou Junyi Li Tianyi Tang Xiaolei Wang Yupeng Hou Yingqian Min Beichen Zhang Junjie Zhang and Zican Dong. 2023. A survey of large language models. arXiv:2303.18223. Retrieved from https:\/\/arxiv.org\/abs\/2303.18223"},{"key":"e_1_3_2_59_2","first-page":"6586","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"Zhao Yue","year":"2023","unstructured":"Yue Zhao, Ishan Misra, Philipp Kr\u00e4henb\u00fchl, and Rohit Girdhar. 2023. Learning video representations from large language models. In Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 6586\u20136597."},{"key":"e_1_3_2_60_2","doi-asserted-by":"crossref","first-page":"1893","DOI":"10.1145\/3340531.3411954","volume-title":"Proceedings of the 29th ACM International Conference on Information & Knowledge Management","author":"Zhou Kun","year":"2020","unstructured":"Kun Zhou, Hui Wang, Wayne Xin Zhao, Yutao Zhu, Sirui Wang, Fuzheng Zhang, Zhongyuan Wang, and Ji-Rong Wen. 2020. S3-rec: Self-supervised learning for sequential recommendation with mutual information maximization. In Proceedings of the 29th ACM International Conference on Information & Knowledge Management, 1893\u20131902."},{"key":"e_1_3_2_61_2","doi-asserted-by":"crossref","first-page":"2337","DOI":"10.1007\/s11263-022-01653-1","article-title":"Learning to prompt for vision-language models","volume":"130","author":"Zhou Kaiyang","year":"2021","unstructured":"Kaiyang Zhou, Jingkang Yang, Chen Change Loy, and Ziwei Liu. 2021. Learning to prompt for vision-language models. International Journal of Computer Vision 130 (2021), 2337\u20132348.","journal-title":"International Journal of Computer Vision"},{"key":"e_1_3_2_62_2","first-page":"2388","volume-title":"Proceedings of the ACM Web Conference","author":"Zhou Kun","year":"2022","unstructured":"Kun Zhou, Hui Yu, Wayne Xin Zhao, and Ji-Rong Wen. 2022. Filter-enhanced MLP is all you need for sequential recommendation. In Proceedings of the ACM Web Conference, 2388\u20132399."},{"issue":"7","key":"e_1_3_2_63_2","first-page":"6901","article-title":"Explainable discrete collaborative filtering","volume":"35","author":"Zhu Lei","year":"2023","unstructured":"Lei Zhu, Yang Xu, Jingjing Li, Weili Guan, and Zhiyong Cheng. 2023. Explainable discrete collaborative filtering. 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