{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,11]],"date-time":"2026-05-11T11:22:54Z","timestamp":1778498574827,"version":"3.51.4"},"publisher-location":"New York, NY, USA","reference-count":40,"publisher":"ACM","license":[{"start":{"date-parts":[[2025,7,20]],"date-time":"2025-07-20T00:00:00Z","timestamp":1752969600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Research Impact Fund","award":["No.R1015-23"],"award-info":[{"award-number":["No.R1015-23"]}]},{"name":"Collaborative Research Fund","award":["No.C1043-24GF"],"award-info":[{"award-number":["No.C1043-24GF"]}]},{"name":"CityU - HKIDS Early Career Research Grant","award":["No.9360163"],"award-info":[{"award-number":["No.9360163"]}]},{"name":"Tencent (CCF-Tencent Open Fund, Tencent Rhino-Bird Focused Research Program)"},{"name":"Hong Kong ITC Innovation and Technology Fund Midstream Research Programme for Universities Project","award":["No.ITS\/034\/22MS"],"award-info":[{"award-number":["No.ITS\/034\/22MS"]}]},{"name":"SIRG - CityU Strategic Interdisciplinary Research Grant","award":["No.7020046"],"award-info":[{"award-number":["No.7020046"]}]},{"name":"Ant Group (CCF-Ant Research Fund, Ant Group Research Fund)"},{"name":"Kuaishou"},{"name":"Hong Kong Environmental and Conservation Fund","award":["No. 88\/2022"],"award-info":[{"award-number":["No. 88\/2022"]}]},{"name":"Alibaba (CCF-Alimama Tech Kangaroo Fund)","award":["No. 2024002"],"award-info":[{"award-number":["No. 2024002"]}]},{"name":"APRC - CityU New Research Initiatives (Start-up Grant for New Faculty of CityU)","award":["No.9610565"],"award-info":[{"award-number":["No.9610565"]}]},{"name":"Huawei (Huawei Innovation Research Program)"},{"name":"CCF-BaiChuan-Ebtech Foundation Model Fund"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,7,20]]},"DOI":"10.1145\/3690624.3709304","type":"proceedings-article","created":{"date-parts":[[2025,4,4]],"date-time":"2025-04-04T18:42:22Z","timestamp":1743792142000},"page":"1948-1959","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":8,"title":["GLINT-RU: Gated Lightweight Intelligent Recurrent Units for Sequential Recommender Systems"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-1758-6708","authenticated-orcid":false,"given":"Sheng","family":"Zhang","sequence":"first","affiliation":[{"name":"City University of Hong Kong, Hong Kong, China & High Magnetic Field Laboratory, Chinese Academy of Sciences, Hefei, Anhui, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0073-0172","authenticated-orcid":false,"given":"Maolin","family":"Wang","sequence":"additional","affiliation":[{"name":"City University of Hong Kong, Hong Kong, Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5976-0707","authenticated-orcid":false,"given":"Wanyu","family":"Wang","sequence":"additional","affiliation":[{"name":"City University of Hong Kong, Hong Kong, Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4470-5972","authenticated-orcid":false,"given":"Jingtong","family":"Gao","sequence":"additional","affiliation":[{"name":"City University of Hong Kong, Hong Kong, Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2926-4416","authenticated-orcid":false,"given":"Xiangyu","family":"Zhao","sequence":"additional","affiliation":[{"name":"City University of Hong Kong, Hong Kong, Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8209-2898","authenticated-orcid":false,"given":"Yu","family":"Yang","sequence":"additional","affiliation":[{"name":"City University of Hong Kong, Hong Kong, Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4450-2251","authenticated-orcid":false,"given":"Xuetao","family":"Wei","sequence":"additional","affiliation":[{"name":"Southern University of Science and Technology, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0491-307X","authenticated-orcid":false,"given":"Zitao","family":"Liu","sequence":"additional","affiliation":[{"name":"Jinan University, Guangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4246-5386","authenticated-orcid":false,"given":"Tong","family":"Xu","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China, Hefei, Anhui, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,7,20]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3580305.3599884"},{"key":"e_1_3_2_2_2_1","volume-title":"Empirical evaluation of gated recurrent neural networks on sequence modeling. arXiv preprint arXiv:1412.3555","author":"Chung Junyoung","year":"2014","unstructured":"Junyoung Chung, Caglar Gulcehre, KyungHyun Cho, and Yoshua Bengio. 2014. Empirical evaluation of gated recurrent neural networks on sequence modeling. arXiv preprint arXiv:1412.3555 (2014)."},{"key":"e_1_3_2_2_3_1","volume-title":"Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models. arXiv preprint arXiv:2402.19427","author":"De Soham","year":"2024","unstructured":"Soham De, Samuel L Smith, Anushan Fernando, Aleksandar Botev, George Cristian-Muraru, Albert Gu, Ruba Haroun, Leonard Berrada, Yutian Chen, Srivatsan Srinivasan, et al. 2024. Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models. arXiv preprint arXiv:2402.19427 (2024)."},{"key":"e_1_3_2_2_4_1","volume-title":"Gate-variants of gated recurrent unit (GRU) neural networks. In 2017 IEEE 60th international midwest symposium on circuits and systems (MWSCAS)","author":"Dey Rahul","unstructured":"Rahul Dey and Fathi M Salem. 2017. Gate-variants of gated recurrent unit (GRU) neural networks. In 2017 IEEE 60th international midwest symposium on circuits and systems (MWSCAS). IEEE, 1597--1600."},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2017.12.012"},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462978"},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3637871"},{"key":"e_1_3_2_2_8_1","volume-title":"Proceedings of the thirteenth international conference on artificial intelligence and statistics. JMLR Workshop and Conference Proceedings, 249--256","author":"Glorot Xavier","year":"2010","unstructured":"Xavier Glorot and Yoshua Bengio. 2010. Understanding the difficulty of training deep feedforward neural networks. In Proceedings of the thirteenth international conference on artificial intelligence and statistics. JMLR Workshop and Conference Proceedings, 249--256."},{"key":"e_1_3_2_2_9_1","volume-title":"Mamba: Linear-time sequence modeling with selective state spaces. arXiv preprint arXiv:2312.00752","author":"Gu Albert","year":"2023","unstructured":"Albert Gu and Tri Dao. 2023. Mamba: Linear-time sequence modeling with selective state spaces. arXiv preprint arXiv:2312.00752 (2023)."},{"key":"e_1_3_2_2_10_1","volume-title":"Session-based recommendations with recurrent neural networks. arXiv preprint arXiv:1511.06939","author":"Hidasi Bal\u00e1zs","year":"2015","unstructured":"Bal\u00e1zs Hidasi, Alexandros Karatzoglou, Linas Baltrunas, and Domonkos Tikk. 2015. Session-based recommendations with recurrent neural networks. arXiv preprint arXiv:1511.06939 (2015)."},{"key":"e_1_3_2_2_11_1","volume-title":"Adaptive mixtures of local experts. Neural computation","author":"Jacobs Robert A","year":"1991","unstructured":"Robert A Jacobs, Michael I Jordan, Steven J Nowlan, and Geoffrey E Hinton. 1991. Adaptive mixtures of local experts. Neural computation, Vol. 3, 1 (1991), 79--87."},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2018.00035"},{"key":"e_1_3_2_2_13_1","volume-title":"Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980","author":"Kingma Diederik P","year":"2014","unstructured":"Diederik P Kingma and Jimmy Ba. 2014. Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)."},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3604915.3608779"},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3132847.3132926"},{"key":"e_1_3_2_2_16_1","volume-title":"MLP4Rec: A pure MLP architecture for sequential recommendations. arXiv preprint arXiv:2204.11510","author":"Li Muyang","year":"2022","unstructured":"Muyang Li, Xiangyu Zhao, Chuan Lyu, Minghao Zhao, Runze Wu, and Ruocheng Guo. 2022. MLP4Rec: A pure MLP architecture for sequential recommendations. arXiv preprint arXiv:2204.11510 (2022)."},{"key":"e_1_3_2_2_17_1","volume-title":"Mamba4Rec: Towards Efficient Sequential Recommendation with Selective State Space Models. arXiv preprint arXiv:2403.03900","author":"Liu Chengkai","year":"2024","unstructured":"Chengkai Liu, Jianghao Lin, Jianling Wang, Hanzhou Liu, and James Caverlee. 2024a. Mamba4Rec: Towards Efficient Sequential Recommendation with Selective State Space Models. arXiv preprint arXiv:2403.03900 (2024)."},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539618.3591717"},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3583780.3614788"},{"key":"e_1_3_2_2_20_1","volume-title":"Bidirectional gated mamba for sequential recommendation. arXiv preprint arXiv:2408.11451","author":"Liu Ziwei","year":"2024","unstructured":"Ziwei Liu, Qidong Liu, Yejing Wang, Wanyu Wang, Pengyue Jia, Maolin Wang, Zitao Liu, Yi Chang, and Xiangyu Zhao. 2024b. Bidirectional gated mamba for sequential recommendation. arXiv preprint arXiv:2408.11451 (2024)."},{"key":"e_1_3_2_2_21_1","volume-title":"Learning Global and Multi-granularity Local Representation with MLP for Sequential Recommendation. ACM Transactions on Knowledge Discovery from Data","author":"Long Chao","year":"2024","unstructured":"Chao Long, Huanhuan Yuan, Junhua Fang, Xuefeng Xian, Guanfeng Liu, Victor S Sheng, and Pengpeng Zhao. 2024. Learning Global and Multi-granularity Local Representation with MLP for Sequential Recommendation. ACM Transactions on Knowledge Discovery from Data, Vol. 18, 4 (2024), 1--15."},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-012-9338-y"},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/3109859.3109896"},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2018.04.298"},{"key":"e_1_3_2_2_25_1","volume-title":"Proceedings of the IEEE\/CVF winter conference on applications of computer vision. 3531--3539","author":"Shen Zhuoran","year":"2021","unstructured":"Zhuoran Shen, Mingyuan Zhang, Haiyu Zhao, Shuai Yi, and Hongsheng Li. 2021. Efficient attention: Attention with linear complexities. In Proceedings of the IEEE\/CVF winter conference on applications of computer vision. 3531--3539."},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3357895"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i5.16564"},{"key":"e_1_3_2_2_28_1","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, Lukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. Advances in Neural Information Processing Systems, Vol. 30 (2017)."},{"key":"e_1_3_2_2_29_1","volume-title":"Linformer: Self-attention with linear complexity. arXiv preprint arXiv:2006.04768","author":"Wang Sinong","year":"2020","unstructured":"Sinong Wang, Belinda Z Li, Madian Khabsa, Han Fang, and Hao Ma. 2020. Linformer: Self-attention with linear complexity. arXiv preprint arXiv:2006.04768 (2020)."},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/3383313.3412258"},{"key":"e_1_3_2_2_31_1","unstructured":"Jiyuan Yang Yuanzi Li Jingyu Zhao Hanbing Wang Muyang Ma Jun Ma Zhaochun Ren Mengqi Zhang Xin Xin Zhumin Chen et al. 2024. Uncovering Selective State Space Model's Capabilities in Lifelong Sequential Recommendation. arXiv preprint arXiv:2403.16371 (2024)."},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3532023"},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/3616855.3635760"},{"key":"e_1_3_2_2_34_1","volume-title":"EASRec: Elastic Architecture Search for Efficient Long-term Sequential Recommender Systems. arXiv preprint arXiv:2402.00390","author":"Zhang Sheng","year":"2024","unstructured":"Sheng Zhang, Maolin Wang, Yao Zhao, Chenyi Zhuang, Jinjie Gu, Ruocheng Guo, Xiangyu Zhao, Zijian Zhang, and Hongzhi Yin. 2024. EASRec: Elastic Architecture Search for Efficient Long-term Sequential Recommender Systems. arXiv preprint arXiv:2402.00390 (2024)."},{"key":"e_1_3_2_2_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/3285029"},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/3543507.3583418"},{"key":"e_1_3_2_2_37_1","volume-title":"Embedding in recommender systems: A survey. arXiv preprint arXiv:2310.18608","author":"Zhao Xiangyu","year":"2023","unstructured":"Xiangyu Zhao, Maolin Wang, Xinjian Zhao, Jiansheng Li, Shucheng Zhou, Dawei Yin, Qing Li, Jiliang Tang, and Ruocheng Guo. 2023a. Embedding in recommender systems: A survey. arXiv preprint arXiv:2310.18608 (2023)."},{"key":"e_1_3_2_2_38_1","volume-title":"Embedding in Recommender Systems: A Survey. arXiv preprint arXiv:2310.18608","author":"Zhao Xiangyu","year":"2023","unstructured":"Xiangyu Zhao, Maolin Wang, Xinjian Zhao, Jiansheng Li, Shucheng Zhou, Dawei Yin, Qing Li, Jiliang Tang, and Ruocheng Guo. 2023b. Embedding in Recommender Systems: A Survey. arXiv preprint arXiv:2310.18608 (2023)."},{"key":"e_1_3_2_2_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3512111"},{"key":"e_1_3_2_2_40_1","unstructured":"You Zhou Xiujing Lin Xiang Zhang Maolin Wang Gangwei Jiang Huakang Lu Yupeng Wu Kai Zhang Zhe Yang Kehang Wang et al. 2023. On the opportunities of green computing: A survey. arXiv preprint arXiv:2311.00447 (2023)."}],"event":{"name":"KDD '25: The 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Toronto ON Canada","acronym":"KDD '25","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"]},"container-title":["Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3690624.3709304","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3690624.3709304","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,16]],"date-time":"2025-08-16T15:36:21Z","timestamp":1755358581000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3690624.3709304"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,20]]},"references-count":40,"alternative-id":["10.1145\/3690624.3709304","10.1145\/3690624"],"URL":"https:\/\/doi.org\/10.1145\/3690624.3709304","relation":{},"subject":[],"published":{"date-parts":[[2025,7,20]]},"assertion":[{"value":"2025-07-20","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}