{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,9]],"date-time":"2025-12-09T08:30:19Z","timestamp":1765269019647,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":39,"publisher":"ACM","license":[{"start":{"date-parts":[[2025,4,22]],"date-time":"2025-04-22T00:00:00Z","timestamp":1745280000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,4,22]]},"DOI":"10.1145\/3696410.3714829","type":"proceedings-article","created":{"date-parts":[[2025,4,22]],"date-time":"2025-04-22T22:47:11Z","timestamp":1745362031000},"page":"304-312","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Unleashing the Potential of Two-Tower Models: Diffusion-Based Cross-Interaction for Large-Scale Matching"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-2462-7831","authenticated-orcid":false,"given":"Yihan","family":"Wang","sequence":"first","affiliation":[{"name":"Kuaishou Technology, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-5359-4639","authenticated-orcid":false,"given":"Fei","family":"Xiong","sequence":"additional","affiliation":[{"name":"Unaffiliated, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-5116-8092","authenticated-orcid":false,"given":"Zhexin","family":"Han","sequence":"additional","affiliation":[{"name":"Kuaishou Technology, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-9670-5693","authenticated-orcid":false,"given":"Qi","family":"Song","sequence":"additional","affiliation":[{"name":"Kuaishou Technology, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-1642-7840","authenticated-orcid":false,"given":"Kaiqiao","family":"Zhan","sequence":"additional","affiliation":[{"name":"Kuaishou Technology, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-1329-3876","authenticated-orcid":false,"given":"Ben","family":"Wang","sequence":"additional","affiliation":[{"name":"Kuaishou Technology, Beijing, China"}]}],"member":"320","published-online":{"date-parts":[[2025,4,22]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","unstructured":"Fedor Borisyuk Krishnaram Kenthapadi David Stein and Bo Zhao. 2016. CaSMoS: A Framework for Learning Candidate Selection Models over Structured Queries and Documents. 441--450. https:\/\/doi.org\/10.1145\/2939672.2939718","DOI":"10.1145\/2939672.2939718"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3512077"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"crossref","unstructured":"Yufei Feng Fuyu Lv Weichen Shen MenghanWang Fei Sun Yu Zhu and Keping Yang. 2019. Deep Session Interest Network for Click-Through Rate Prediction. arXiv:1905.06482 [cs.IR] https:\/\/arxiv.org\/abs\/1905.06482","DOI":"10.24963\/ijcai.2019\/319"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3511808.3557624"},{"key":"e_1_3_2_1_5_1","volume-title":"New Loss Functions for Fast Maximum Inner Product Search. CoRR abs\/1908.10396","author":"Guo Ruiqi","year":"2019","unstructured":"Ruiqi Guo, Quan Geng, David Simcha, Felix Chern, Sanjiv Kumar, and Xiang Wu. 2019. New Loss Functions for Fast Maximum Inner Product Search. CoRR abs\/1908.10396 (2019). arXiv:1908.10396 http:\/\/arxiv.org\/abs\/1908.10396"},{"key":"e_1_3_2_1_6_1","article-title":"The MovieLens Datasets","volume":"5","author":"Harper F. Maxwell","year":"2016","unstructured":"F. Maxwell Harper, Joseph A. Konstan, and Joseph A. 2016. The MovieLens Datasets: History and Context. ACM Trans. Interact. Intell. Syst. 5 (2016), 19:1--19:19. https:\/\/api.semanticscholar.org\/CorpusID:16619709","journal-title":"History and Context. ACM Trans. Interact. Intell. Syst."},{"key":"e_1_3_2_1_7_1","unstructured":"Bal\u00e1zs Hidasi Alexandros Karatzoglou Linas Baltrunas and Domonkos Tikk. 2016. Session-based Recommendations with Recurrent Neural Networks. arXiv:1511.06939 [cs.LG]"},{"key":"e_1_3_2_1_8_1","volume-title":"International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=Sy2fzU9gl","author":"Higgins Irina","year":"2017","unstructured":"Irina Higgins, Loic Matthey, Arka Pal, Christopher Burgess, Xavier Glorot, Matthew Botvinick, Shakir Mohamed, and Alexander Lerchner. 2017. beta-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework. In International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=Sy2fzU9gl"},{"key":"e_1_3_2_1_9_1","volume-title":"Lin (Eds.)","volume":"33","author":"Ho Jonathan","year":"2020","unstructured":"Jonathan Ho, Ajay Jain, and Pieter Abbeel. 2020. Denoising Diffusion Probabilistic Models. In Advances in Neural Information Processing Systems, H. Larochelle, M. Ranzato, R. Hadsell, M.F. Balcan, and H. Lin (Eds.), Vol. 33. Curran Associates, Inc., 6840--6851. https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2020\/file\/4c5bcfec8584af0d967f1ab10179ca4b-Paper.pdf"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"crossref","unstructured":"Yu Hou Jin-Duk Park and Won-Yong Shin. 2024. Collaborative Filtering Based on Diffusion Models: Unveiling the Potential of High-Order Connectivity. arXiv:2404.14240 [cs.IR] https:\/\/arxiv.org\/abs\/2404.14240","DOI":"10.1145\/3626772.3657742"},{"key":"e_1_3_2_1_11_1","volume-title":"Exploration in two-stage recommender systems. CoRR abs\/2009.08956","author":"Hron Jiri","year":"2020","unstructured":"Jiri Hron, Karl Krauth, Michael I. Jordan, and Niki Kilbertus. 2020. Exploration in two-stage recommender systems. CoRR abs\/2009.08956 (2020). arXiv:2009.08956 https:\/\/arxiv.org\/abs\/2009.08956"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403305"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/2505515.2505665"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3503161.3547855"},{"key":"e_1_3_2_1_15_1","volume-title":"Billion-scale similarity search with GPUs. CoRR abs\/1702.08734","author":"Johnson Jeff","year":"2017","unstructured":"Jeff Johnson, Matthijs Douze, and Herv\u00e9 J\u00e9gou. 2017. Billion-scale similarity search with GPUs. CoRR abs\/1702.08734 (2017). arXiv:1702.08734 http:\/\/arxiv. org\/abs\/1702.08734"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2018.00035"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"crossref","unstructured":"Omar Khattab and Matei Zaharia. 2020. ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT. arXiv:2004.12832 [cs.IR]","DOI":"10.1145\/3397271.3401075"},{"key":"e_1_3_2_1_18_1","unstructured":"Xiangyang Li Bo Chen HuiFeng Guo Jingjie Li Chenxu Zhu Xiang Long Sujian Li Yichao Wang Wei Guo Longxia Mao Jinxing Liu Zhenhua Dong and Ruiming Tang. 2022. IntTower: the Next Generation of Two-Tower Model for Pre-Ranking System. arXiv:2210.09890 [cs.IR]"},{"key":"e_1_3_2_1_19_1","unstructured":"Zihao Li Aixin Sun and Chenliang Li. 2023. DiffuRec: A Diffusion Model for Sequential Recommendation. arXiv:2304.00686 [cs.IR]"},{"key":"e_1_3_2_1_20_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. 2024. Mamba4rec: Towards efficient sequential recommendation with selective state space models. arXiv preprint arXiv:2403.03900 (2024)."},{"key":"e_1_3_2_1_21_1","unstructured":"Calvin Luo. 2022. Understanding Diffusion Models: A Unified Perspective. arXiv:2208.11970 [cs.LG]"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462979"},{"key":"e_1_3_2_1_23_1","volume-title":"SimpleX: A Simple and Strong Baseline for Collaborative Filtering. CoRR abs\/2109.12613","author":"Mao Kelong","year":"2021","unstructured":"Kelong Mao, Jieming Zhu, Jinpeng Wang, Quanyu Dai, Zhenhua Dong, Xi Xiao, and Xiuqiang He. 2021. SimpleX: A Simple and Strong Baseline for Collaborative Filtering. CoRR abs\/2109.12613 (2021). arXiv:2109.12613 https:\/\/arxiv.org\/abs\/2109.12613"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01042"},{"key":"e_1_3_2_1_25_1","volume-title":"Denoising Diffusion Implicit Models. In International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=St1giarCHLP","author":"Song Jiaming","year":"2021","unstructured":"Jiaming Song, Chenlin Meng, and Stefano Ermon. 2021. Denoising Diffusion Implicit Models. In International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=St1giarCHLP"},{"key":"e_1_3_2_1_26_1","unstructured":"Liangcai Su Fan Yan Jieming Zhu Xi Xiao Haoyi Duan Zhou Zhao Zhenhua Dong and Ruiming Tang. 2023. Beyond Two-Tower Matching: Learning Sparse Retrievable Cross-Interactions for Recommendation. arXiv:2311.18213 [cs.IR]"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3357895"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3159652.3159656"},{"key":"e_1_3_2_1_29_1","volume-title":"Advances in Neural Information Processing Systems","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. In Advances in Neural Information Processing Systems, I. Guyon, U. Von Luxburg, S. Bengio, H.Wallach, R. Fergus, S. Vishwanathan, and R. Garnett (Eds.), Vol. 30. Curran Associates, Inc. https:\/\/proceedings.neurips.cc\/paper_files\/paper\/2017\/file\/3f5ee243547dee91fbd053c1c4a845aa-Paper.pdf"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539618.3591663"},{"key":"e_1_3_2_1_31_1","volume-title":"Proceedings of the 31st ACM International Conference on Information & Knowledge Management. 2056--2066","author":"Zhang Hengrui","year":"2022","unstructured":"YuWang, Hengrui Zhang, Zhiwei Liu, Liangwei Yang, and Philip S Yu. 2022. Contrastvae: Contrastive variational autoencoder for sequential recommendation. In Proceedings of the 31st ACM International Conference on Information & Knowledge Management. 2056--2066."},{"key":"e_1_3_2_1_32_1","volume-title":"COLD: Towards the Next Generation of Pre-Ranking System. arXiv:2007.16122 [cs.IR]","author":"Wang Zhe","year":"2020","unstructured":"Zhe Wang, Liqin Zhao, Biye Jiang, Guorui Zhou, Xiaoqiang Zhu, and Kun Gai. 2020. COLD: Towards the Next Generation of Pre-Ranking System. arXiv:2007.16122 [cs.IR]"},{"key":"e_1_3_2_1_33_1","volume-title":"Lichan Hong, Yang Li, Simon Wang, Taibai Xu, and Ed H. Chi.","author":"Yang Ji","year":"2020","unstructured":"Ji Yang, Xinyang Yi, Derek Zhiyuan Cheng, Lichan Hong, Yang Li, Simon Wang, Taibai Xu, and Ed H. Chi. 2020. Mixed Negative Sampling for Learning Two-tower Neural Networks in Recommendations."},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/3298689.3346996"},{"key":"e_1_3_2_1_35_1","volume-title":"A dual augmented two-tower model for online large-scale recommendation. DLP-KDD","author":"Yu Yantao","year":"2021","unstructured":"Yantao Yu, Weipeng Wang, Zhoutian Feng, and Daiyue Xue. 2021. A dual augmented two-tower model for online large-scale recommendation. DLP-KDD (2021)."},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"crossref","unstructured":"Yuan Zhang Xue Dong Weijie Ding Biao Li Peng Jiang and Kun Gai. 2023. Divide and Conquer: Towards Better Embedding-based Retrieval for Recommender Systems From a Multi-task Perspective. arXiv:2302.02657 [cs.IR]","DOI":"10.1145\/3543873.3584629"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"crossref","unstructured":"Guorui Zhou Na Mou Ying Fan Qi Pi Weijie Bian Chang Zhou Xiaoqiang Zhu and Kun Gai. 2018. Deep Interest Evolution Network for Click-Through Rate Prediction. arXiv:1809.03672 [stat.ML]","DOI":"10.1609\/aaai.v33i01.33015941"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219823"},{"key":"e_1_3_2_1_39_1","unstructured":"Yunqin Zhu ChaoWang Qi Zhang and Hui Xiong. 2024. Graph Signal Diffusion Model for Collaborative Filtering. arXiv:2311.08744 [cs.IR] https:\/\/arxiv.org\/abs\/2311.08744"}],"event":{"name":"WWW '25: The ACM Web Conference 2025","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"],"location":"Sydney NSW Australia","acronym":"WWW '25"},"container-title":["Proceedings of the ACM on Web Conference 2025"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3696410.3714829","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3696410.3714829","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T01:18:42Z","timestamp":1750295922000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3696410.3714829"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,22]]},"references-count":39,"alternative-id":["10.1145\/3696410.3714829","10.1145\/3696410"],"URL":"https:\/\/doi.org\/10.1145\/3696410.3714829","relation":{},"subject":[],"published":{"date-parts":[[2025,4,22]]},"assertion":[{"value":"2025-04-22","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}