{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T03:12:34Z","timestamp":1774926754528,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":52,"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\/3696410.3714955","type":"proceedings-article","created":{"date-parts":[[2025,4,22]],"date-time":"2025-04-22T22:52:18Z","timestamp":1745362338000},"page":"425-435","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Distinguished Quantized Guidance for Diffusion-based Sequence Recommendation"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-1348-8412","authenticated-orcid":false,"given":"Wenyu","family":"Mao","sequence":"first","affiliation":[{"name":"Kuaishou Technology, Beijing, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1440-911X","authenticated-orcid":false,"given":"Shuchang","family":"Liu","sequence":"additional","affiliation":[{"name":"Kuaishou Technology, Beijing, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-8594-4045","authenticated-orcid":false,"given":"Haoyang","family":"Liu","sequence":"additional","affiliation":[{"name":"Researcher, Hefei, Anhui, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-3979-8628","authenticated-orcid":false,"given":"Haozhe","family":"Liu","sequence":"additional","affiliation":[{"name":"Researcher, Hefei, Anhui, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-6958-3388","authenticated-orcid":false,"given":"Xiang","family":"Li","sequence":"additional","affiliation":[{"name":"Kuaishou Technology, Beijing, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0697-8985","authenticated-orcid":false,"given":"Lantao","family":"Hu","sequence":"additional","affiliation":[{"name":"Kuaishou Technology, Beijing, Beijing, China"}]}],"member":"320","published-online":{"date-parts":[[2025,4,22]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"Alexei Baevski Steffen Schneider and Michael Auli. 2020. vq-wav2vec: Self-Supervised Learning of Discrete Speech Representations. In ICLR. OpenReview.net."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"crossref","unstructured":"Yukuo Cen Jianwei Zhang Xu Zou Chang Zhou Hongxia Yang and Jie Tang. 2020. Controllable Multi-Interest Framework for Recommendation. In KDD. ACM 2942--2951.","DOI":"10.1145\/3394486.3403344"},{"key":"e_1_3_2_1_3_1","unstructured":"Prafulla Dhariwal and Alexander Quinn Nichol. 2021. Diffusion Models Beat GANs on Image Synthesis. In NeurIPS. 8780--8794."},{"key":"e_1_3_2_1_4_1","unstructured":"Huanshuo Dong Hong Wang Haoyang Liu Jian Luo and Jie Wang. 2024. Accelerating PDE Data Generation via Differential Operator Action in Solution Space. In ICML. OpenReview.net."},{"key":"e_1_3_2_1_5_1","volume-title":"Yu","author":"Fan Ziwei","year":"2022","unstructured":"Ziwei Fan, Zhiwei Liu, Yu Wang, Alice Wang, Zahra Nazari, Lei Zheng, Hao Peng, and Philip S. Yu. 2022. Sequential Recommendation via Stochastic Self-Attention. In WWW. ACM, 2036--2047."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"crossref","unstructured":"Chongming Gao Kexin Huang Jiawei Chen Yuan Zhang Biao Li Peng Jiang Shiqi Wang Zhong Zhang and Xiangnan He. 2023. Alleviating Matthew Effect of Offline Reinforcement Learning in Interactive Recommendation. In SIGIR. ACM 238--248.","DOI":"10.1145\/3539618.3591636"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3594871"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3422622"},{"key":"e_1_3_2_1_9_1","unstructured":"Bal\u00e1zs Hidasi Alexandros Karatzoglou Linas Baltrunas and Domonkos Tikk. 2016. Session-based Recommendations with Recurrent Neural Networks. In ICLR (Poster)."},{"key":"e_1_3_2_1_10_1","unstructured":"Jonathan Ho Ajay Jain and Pieter Abbeel. 2020. Denoising Diffusion Probabilistic Models. In NeurIPS."},{"key":"e_1_3_2_1_11_1","volume-title":"MDM: Molecular Diffusion Model for 3D Molecule Generation","author":"Huang Lei","year":"2023","unstructured":"Lei Huang, Hengtong Zhang, Tingyang Xu, and Ka-Chun Wong. 2023b. MDM: Molecular Diffusion Model for 3D Molecule Generation. In AAAI. AAAI Press, 5105--5112."},{"key":"e_1_3_2_1_12_1","volume-title":"Towards Accurate Image Coding: Improved Autoregressive Image Generation with Dynamic Vector Quantization","author":"Huang Mengqi","unstructured":"Mengqi Huang, Zhendong Mao, Zhuowei Chen, and Yongdong Zhang. 2023a. Towards Accurate Image Coding: Improved Autoregressive Image Generation with Dynamic Vector Quantization. In CVPR. IEEE, 22596--22605."},{"key":"e_1_3_2_1_13_1","unstructured":"Eric Jang Shixiang Gu and Ben Poole. 2017. Categorical Reparameterization with Gumbel-Softmax. In ICLR (Poster). OpenReview.net."},{"key":"e_1_3_2_1_14_1","volume-title":"McAuley","author":"Kang Wang-Cheng","year":"2018","unstructured":"Wang-Cheng Kang and Julian J. McAuley. 2018. Self-Attentive Sequential Recommendation. In ICDM. IEEE Computer Society, 197--206."},{"key":"e_1_3_2_1_15_1","volume-title":"Rethinking Branching on Exact Combinatorial Optimization Solver: The First Deep Symbolic Discovery Framework. In The Twelfth International Conference on Learning Representations.","author":"Kuang Yufei","year":"2024","unstructured":"Yufei Kuang, Jie Wang, Haoyang Liu, Fangzhou Zhu, Xijun Li, Jia Zeng, HAO Jianye, Bin Li, and Feng Wu. 2024. Rethinking Branching on Exact Combinatorial Optimization Solver: The First Deep Symbolic Discovery Framework. In The Twelfth International Conference on Learning Representations."},{"key":"e_1_3_2_1_16_1","volume-title":"DiffGAD: A Diffusion-based Unsupervised Graph Anomaly Detector. CoRR","author":"Li Jinghan","year":"2024","unstructured":"Jinghan Li, Yuan Gao, Jinda Lu, Junfeng Fang, Congcong Wen, Hui Lin, and Xiang Wang. 2024b. DiffGAD: A Diffusion-based Unsupervised Graph Anomaly Detector. CoRR, Vol. abs\/2410.06549 (2024)."},{"key":"e_1_3_2_1_17_1","volume-title":"McAuley","author":"Li Jiacheng","year":"2022","unstructured":"Jiacheng Li, Tong Zhao, Jin Li, Jim Chan, Christos Faloutsos, George Karypis, Soo-Min Pantel, and Julian J. McAuley. 2022. Coarse-to-Fine Sparse Sequential Recommendation. In SIGIR. ACM, 2082--2086."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"crossref","unstructured":"Xuewei Li Hongwei Chen Jian Yu Mankun Zhao Tianyi Xu Wenbin Zhang and Mei Yu. 2024a. Global Heterogeneous Graph and Target Interest Denoising for Multi-behavior Sequential Recommendation. In WSDM. ACM 387--395.","DOI":"10.1145\/3616855.3635857"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3631116"},{"key":"e_1_3_2_1_20_1","volume-title":"Promoting Generalization for Exact Solvers via Adversarial Instance Augmentation. CoRR","author":"Liu Haoyang","year":"2023","unstructured":"Haoyang Liu, Yufei Kuang, Jie Wang, Xijun Li, Yongdong Zhang, and Feng Wu. 2023a. Promoting Generalization for Exact Solvers via Adversarial Instance Augmentation. CoRR, Vol. abs\/2310.14161 (2023)."},{"key":"e_1_3_2_1_21_1","unstructured":"Haoyang Liu Jie Wang Zijie Geng Xijun Li Yuxuan Zong Fangzhou Zhu Jianye HAO and Feng Wu. 2025. Apollo-MILP: An Alternating Prediction-Correction Neural Solving Framework for Mixed-Integer Linear Programming. In The Thirteenth International Conference on Learning Representations. https:\/\/openreview.net\/forum?id=mFY0tPDWK8"},{"key":"e_1_3_2_1_22_1","volume-title":"The Thirty-eighth Annual Conference on Neural Information Processing Systems. https:\/\/openreview.net\/forum?id=W433RI0VU4","author":"Liu Haoyang","year":"2024","unstructured":"Haoyang Liu, Jie Wang, Wanbo Zhang, Zijie Geng, Yufei Kuang, Xijun Li, Bin Li, Yongdong Zhang, and Feng Wu. 2024b. MILP-StuDio: MILP Instance Generation via Block Structure Decomposition. In The Thirty-eighth Annual Conference on Neural Information Processing Systems. https:\/\/openreview.net\/forum?id=W433RI0VU4"},{"key":"e_1_3_2_1_23_1","volume-title":"DIDI: Diffusion-Guided Diversity for Offline Behavioral Generation. In ICML. OpenReview.net.","author":"Liu Jinxin","year":"2024","unstructured":"Jinxin Liu, Xinghong Guo, Zifeng Zhuang, and Donglin Wang. 2024a. DIDI: Diffusion-Guided Diversity for Offline Behavioral Generation. In ICML. OpenReview.net."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/3589334.3645484"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"crossref","unstructured":"Qidong Liu Fan Yan Xiangyu Zhao Zhaocheng Du Huifeng Guo Ruiming Tang and Feng Tian. 2023b. Diffusion Augmentation for Sequential Recommendation. In CIKM. ACM 1576--1586.","DOI":"10.1145\/3583780.3615134"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.2401.16433nolinkurl10.48550"},{"key":"e_1_3_2_1_27_1","volume-title":"Plug-In Diffusion Model for Sequential Recommendation","author":"Ma Haokai","unstructured":"Haokai Ma, Ruobing Xie, Lei Meng, Xin Chen, Xu Zhang, Leyu Lin, and Zhanhui Kang. 2024. Plug-In Diffusion Model for Sequential Recommendation. In AAAI. AAAI Press, 8886--8894."},{"key":"e_1_3_2_1_28_1","volume-title":"Reinforced Prompt Personalization for Recommendation with Large Language Models. CoRR","author":"Mao Wenyu","year":"2024","unstructured":"Wenyu Mao, Jiancan Wu, Weijian Chen, Chongming Gao, Xiang Wang, and Xiangnan He. 2024a. Reinforced Prompt Personalization for Recommendation with Large Language Models. CoRR, Vol. abs\/2407.17115 (2024)."},{"key":"e_1_3_2_1_29_1","volume-title":"Invariant Graph Learning Meets Information Bottleneck for Out-of-Distribution Generalization. CoRR","author":"Mao Wenyu","year":"2024","unstructured":"Wenyu Mao, Jiancan Wu, Haoyang Liu, Yongduo Sui, and Xiang Wang. 2024b. Invariant Graph Learning Meets Information Bottleneck for Out-of-Distribution Generalization. CoRR, Vol. abs\/2408.01697 (2024)."},{"key":"e_1_3_2_1_30_1","volume-title":"Training Diffusion Models Towards Diverse Image Generation with Reinforcement Learning","author":"Miao Zichen","unstructured":"Zichen Miao, Jiang Wang, Ze Wang, Zhengyuan Yang, Lijuan Wang, Qiang Qiu, and Zicheng Liu. 2024. Training Diffusion Models Towards Diverse Image Generation with Reinforcement Learning. In CVPR. IEEE, 10844--10853."},{"key":"e_1_3_2_1_31_1","volume-title":"Albert Ali Salah, and Itir \u00d6nal Ertugrul","author":"Ning Mang","year":"2024","unstructured":"Mang Ning, Mingxiao Li, Jianlin Su, Albert Ali Salah, and Itir \u00d6nal Ertugrul. 2024. Elucidating the Exposure Bias in Diffusion Models. In ICLR. OpenReview.net."},{"key":"e_1_3_2_1_32_1","volume-title":"Click-through Rate Prediction with Auto-Quantized Contrastive Learning. CoRR","author":"Pan Yujie","year":"2021","unstructured":"Yujie Pan, Jiangchao Yao, Bo Han, Kunyang Jia, Ya Zhang, and Hongxia Yang. 2021. Click-through Rate Prediction with Auto-Quantized Contrastive Learning. CoRR, Vol. abs\/2109.13921 (2021). showeprint[arXiv]2109.13921 https:\/\/arxiv.org\/abs\/2109.13921"},{"key":"e_1_3_2_1_33_1","volume-title":"Scalable Diffusion Models with Transformers","author":"Peebles William","unstructured":"William Peebles and Saining Xie. 2023. Scalable Diffusion Models with Transformers. In ICCV. IEEE, 4172--4182."},{"key":"e_1_3_2_1_34_1","unstructured":"Yunchen Pu Zhe Gan Ricardo Henao Xin Yuan Chunyuan Li Andrew Stevens and Lawrence Carin. 2016. Variational Autoencoder for Deep Learning of Images Labels and Captions. In NIPS. 2352--2360."},{"key":"e_1_3_2_1_35_1","volume-title":"Class-Balancing Diffusion Models","author":"Qin Yiming","year":"1843","unstructured":"Yiming Qin, Huangjie Zheng, Jiangchao Yao, Mingyuan Zhou, and Ya Zhang. 2023. Class-Balancing Diffusion Models. In CVPR. IEEE, 18434--18443."},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"crossref","unstructured":"Ruihong Qiu Zi Huang Hongzhi Yin and Zijian Wang. 2022. Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation. In WSDM. ACM 813--823.","DOI":"10.1145\/3488560.3498433"},{"key":"e_1_3_2_1_37_1","volume-title":"Hui Wang, Bolin Ding, and Ji-Rong Wen.","author":"Ren Ruiyang","year":"2020","unstructured":"Ruiyang Ren, Zhaoyang Liu, Yaliang Li, Wayne Xin Zhao, Hui Wang, Bolin Ding, and Ji-Rong Wen. 2020. Sequential Recommendation with Self-Attentive Multi-Adversarial Network. In SIGIR. ACM, 89--98."},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"crossref","unstructured":"Noveen Sachdeva Giuseppe Manco Ettore Ritacco and Vikram Pudi. 2019. Sequential Variational Autoencoders for Collaborative Filtering. In WSDM. ACM 600--608.","DOI":"10.1145\/3289600.3291007"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/3644392"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"crossref","unstructured":"Fei Sun Jun Liu Jian Wu Changhua Pei Xiao Lin Wenwu Ou and Peng Jiang. 2019. BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer. In CIKM. ACM 1441--1450.","DOI":"10.1145\/3357384.3357895"},{"key":"e_1_3_2_1_41_1","unstructured":"A\u00e4ron van den Oord Oriol Vinyals and Koray Kavukcuoglu. 2017. Neural Discrete Representation Learning. In NIPS. 6306--6315."},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/3511808.3557464"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"crossref","unstructured":"Wenjie Wang Yiyan Xu Fuli Feng Xinyu Lin Xiangnan He and Tat-Seng Chua. 2023b. Diffusion Recommender Model. In SIGIR. ACM 832--841.","DOI":"10.1145\/3539618.3591663"},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"crossref","unstructured":"Xiaobei Wang Shuchang Liu Xueliang Wang Qingpeng Cai Lantao Hu Han Li Peng Jiang Kun Gai and Guangming Xie. 2024. Future Impact Decomposition in Request-level Recommendations. In KDD. ACM 5905--5916.","DOI":"10.1145\/3637528.3671506"},{"key":"e_1_3_2_1_45_1","volume-title":"Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models. In NeurIPS.","author":"Wang Zhendong","year":"2023","unstructured":"Zhendong Wang, Yifan Jiang, Huangjie Zheng, Peihao Wang, Pengcheng He, Zhangyang Wang, Weizhu Chen, and Mingyuan Zhou. 2023a. Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models. In NeurIPS."},{"key":"e_1_3_2_1_46_1","volume-title":"Contrastive Learning for Sequential Recommendation","author":"Xie Xu","unstructured":"Xu Xie, Fei Sun, Zhaoyang Liu, Shiwen Wu, Jinyang Gao, Jiandong Zhang, Bolin Ding, and Bin Cui. 2022. Contrastive Learning for Sequential Recommendation. In ICDE. IEEE, 1259--1273."},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"crossref","unstructured":"Zhe Xie Chengxuan Liu Yichi Zhang Hongtao Lu Dong Wang and Yue Ding. 2021. Adversarial and Contrastive Variational Autoencoder for Sequential Recommendation. In WWW. ACM \/ IW3C2 449--459.","DOI":"10.1145\/3442381.3449873"},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"crossref","unstructured":"Yuhao Yang Chao Huang Lianghao Xia Chunzhen Huang Da Luo and Kangyi Lin. 2023a. Debiased Contrastive Learning for Sequential Recommendation. In WWW. ACM 1063--1073.","DOI":"10.1145\/3543507.3583361"},{"key":"e_1_3_2_1_49_1","unstructured":"Zhengyi Yang Jiancan Wu Zhicai Wang Xiang Wang Yancheng Yuan and Xiangnan He. 2023b. Generate What You Prefer: Reshaping Sequential Recommendation via Guided Diffusion. In NeurIPS."},{"key":"e_1_3_2_1_50_1","volume-title":"Regularized Vector Quantization for Tokenized Image Synthesis","author":"Zhang Jiahui","year":"1846","unstructured":"Jiahui Zhang, Fangneng Zhan, Christian Theobalt, and Shijian Lu. 2023b. Regularized Vector Quantization for Tokenized Image Synthesis. In CVPR. IEEE, 18467--18476."},{"key":"e_1_3_2_1_51_1","volume-title":"Adding Conditional Control to Text-to-Image Diffusion Models","author":"Zhang Lvmin","unstructured":"Lvmin Zhang, Anyi Rao, and Maneesh Agrawala. 2023a. Adding Conditional Control to Text-to-Image Diffusion Models. In ICCV. IEEE, 3813--3824."},{"key":"e_1_3_2_1_52_1","doi-asserted-by":"crossref","unstructured":"Guorui Zhou Xiaoqiang Zhu Chengru Song Ying Fan Han Zhu Xiao Ma Yanghui Yan Junqi Jin Han Li and Kun Gai. 2018. Deep Interest Network for Click-Through Rate Prediction. In KDD. ACM 1059--1068.","DOI":"10.1145\/3219819.3219823"}],"event":{"name":"WWW '25: The ACM Web Conference 2025","location":"Sydney NSW Australia","acronym":"WWW '25","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"]},"container-title":["Proceedings of the ACM on Web Conference 2025"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3696410.3714955","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3696410.3714955","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T01:18:54Z","timestamp":1750295934000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3696410.3714955"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,22]]},"references-count":52,"alternative-id":["10.1145\/3696410.3714955","10.1145\/3696410"],"URL":"https:\/\/doi.org\/10.1145\/3696410.3714955","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"}}]}}