{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,9]],"date-time":"2026-05-09T07:58:28Z","timestamp":1778313508951,"version":"3.51.4"},"publisher-location":"New York, NY, USA","reference-count":79,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,8,24]],"date-time":"2024-08-24T00:00:00Z","timestamp":1724457600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/https:\/\/doi.org\/10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62202443, U23A20319, 62207031"],"award-info":[{"award-number":["62202443, U23A20319, 62207031"]}],"id":[{"id":"10.13039\/https:\/\/doi.org\/10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Anhui Provincial Science and Technology Major Project","award":["2023z020006"],"award-info":[{"award-number":["2023z020006"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,8,25]]},"DOI":"10.1145\/3637528.3671841","type":"proceedings-article","created":{"date-parts":[[2024,8,25]],"date-time":"2024-08-25T04:54:55Z","timestamp":1724561695000},"page":"3954-3965","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":27,"title":["Dataset Regeneration for Sequential Recommendation"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-0853-1089","authenticated-orcid":false,"given":"Mingjia","family":"Yin","sequence":"first","affiliation":[{"name":"University of Science and Technology of China & State Key Laboratory of Cognitive Intelligence, Hefei, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9921-2078","authenticated-orcid":false,"given":"Hao","family":"Wang","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China & State Key Laboratory of Cognitive Intelligence, Hefei, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8616-0221","authenticated-orcid":false,"given":"Wei","family":"Guo","sequence":"additional","affiliation":[{"name":"Huawei Singapore Research Center, Singapore, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9031-9696","authenticated-orcid":false,"given":"Yong","family":"Liu","sequence":"additional","affiliation":[{"name":"Huawei Singapore Research Center, Singapore, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-2193-2288","authenticated-orcid":false,"given":"Suojuan","family":"Zhang","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China & State Key Laboratory of Cognitive Intelligence, Hefei, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8103-0321","authenticated-orcid":false,"given":"Sirui","family":"Zhao","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China & State Key Laboratory of Cognitive Intelligence, Hefei, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3507-9607","authenticated-orcid":false,"given":"Defu","family":"Lian","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China & State Key Laboratory of Cognitive Intelligence, Hefei, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4835-4102","authenticated-orcid":false,"given":"Enhong","family":"Chen","sequence":"additional","affiliation":[{"name":"University of Science and Technology of China & State Key Laboratory of Cognitive Intelligence, Hefei, China"}]}],"member":"320","published-online":{"date-parts":[[2024,8,24]]},"reference":[{"key":"e_1_3_2_2_1_1","volume-title":"Foster","author":"Bauer Andr\u00e9","year":"2024","unstructured":"Andr\u00e9 Bauer, Simon Trapp, Michael Stenger, Robert Leppich, Samuel Kounev, Mark Leznik, Kyle Chard, and Ian T. Foster. 2024. Comprehensive Exploration of Synthetic Data Generation: A Survey. CoRR abs\/2401.02524 (2024)."},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3543507.3583494"},{"key":"e_1_3_2_2_3_1","volume-title":"Intent Contrastive Learning for Sequential Recommendation. In WWW '22: The ACM Web Conference 2022","author":"Chen Yongjun","year":"2022","unstructured":"Yongjun Chen, Zhiwei Liu, Jia Li, Julian J. McAuley, and Caiming Xiong. 2022. Intent Contrastive Learning for Sequential Recommendation. In WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25 - 29, 2022. ACM, 2172--2182."},{"key":"e_1_3_2_2_4_1","volume-title":"Graph Trend Filtering Networks for Recommendation. In SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval","author":"Fan Wenqi","year":"2022","unstructured":"Wenqi Fan, Xiaorui Liu, Wei Jin, Xiangyu Zhao, Jiliang Tang, and Qing Li. 2022. Graph Trend Filtering Networks for Recommendation. In SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11 - 15, 2022. 112--121."},{"key":"e_1_3_2_2_5_1","volume-title":"Sherjil Ozair, Aaron C. Courville, and Yoshua Bengio.","author":"Goodfellow Ian J.","year":"2014","unstructured":"Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde- Farley, Sherjil Ozair, Aaron C. Courville, and Yoshua Bengio. 2014. Generative Adversarial Networks. CoRR abs\/1406.2661 (2014)."},{"key":"e_1_3_2_2_6_1","volume-title":"Towards Lossless Dataset Distillation via Difficulty-Aligned Trajectory Matching. CoRR abs\/2310.05773","author":"Guo Ziyao","year":"2023","unstructured":"Ziyao Guo, KaiWang, George Cazenavette, Hui Li, Kaipeng Zhang, and Yang You. 2023. Towards Lossless Dataset Distillation via Difficulty-Aligned Trajectory Matching. CoRR abs\/2310.05773 (2023)."},{"key":"e_1_3_2_2_7_1","volume-title":"END4Rec: Efficient Noise-Decoupling for Multi-Behavior Sequential Recommendation. CoRR abs\/2403.17603","author":"Han Yongqiang","year":"2024","unstructured":"Yongqiang Han, Hao Wang, Kefan Wang, Likang Wu, Zhi Li, Wei Guo, Yong Liu, Defu Lian, and Enhong Chen. 2024. END4Rec: Efficient Noise-Decoupling for Multi-Behavior Sequential Recommendation. CoRR abs\/2403.17603 (2024)."},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401063"},{"key":"e_1_3_2_2_9_1","volume-title":"4th International Conference on Learning Representations, ICLR","author":"Hidasi Bal\u00e1zs","year":"2016","unstructured":"Bal\u00e1zs Hidasi, Alexandros Karatzoglou, Linas Baltrunas, and Domonkos Tikk. 2016. Session-based Recommendations with Recurrent Neural Networks. In 4th International Conference on Learning Representations, ICLR 2016, San Juan, Puerto Rico, May 2--4, 2016, Conference Track Proceedings."},{"key":"e_1_3_2_2_10_1","volume-title":"Denoising Diffusion Probabilistic Models. In Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020","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 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6--12, 2020, virtual."},{"key":"e_1_3_2_2_11_1","article-title":"Cascaded Diffusion Models for High Fidelity Image Generation","volume":"23","author":"Ho Jonathan","year":"2022","unstructured":"Jonathan Ho, Chitwan Saharia, William Chan, David J. Fleet, Mohammad Norouzi, and Tim Salimans. 2022. Cascaded Diffusion Models for High Fidelity Image Generation. J. Mach. Learn. Res. 23 (2022), 47:1--47:33.","journal-title":"J. Mach. Learn. Res."},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00165"},{"key":"e_1_3_2_2_13_1","volume-title":"Towards Universal Sequence Representation Learning for Recommender Systems. In KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","author":"Hou Yupeng","year":"2022","unstructured":"Yupeng Hou, Shanlei Mu, Wayne Xin Zhao, Yaliang Li, Bolin Ding, and Ji-Rong Wen. 2022. Towards Universal Sequence Representation Learning for Recommender Systems. In KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14 - 18, 2022. ACM, 585--593."},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/ASRU.2017.8268911"},{"key":"e_1_3_2_2_15_1","volume-title":"Categorical Reparameterization with Gumbel-Softmax. In 5th International Conference on Learning Representations, ICLR 2017, Toulon, France, April 24--26, 2017, Conference Track Proceedings.","author":"Jang Eric","year":"2017","unstructured":"Eric Jang, Shixiang Gu, and Ben Poole. 2017. Categorical Reparameterization with Gumbel-Softmax. In 5th International Conference on Learning Representations, ICLR 2017, Toulon, France, April 24--26, 2017, Conference Track Proceedings."},{"key":"e_1_3_2_2_16_1","volume-title":"Graph Structure Learning for Robust Graph Neural Networks. In KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","author":"Jin Wei","year":"2020","unstructured":"Wei Jin, Yao Ma, Xiaorui Liu, Xianfeng Tang, Suhang Wang, and Jiliang Tang. 2020. Graph Structure Learning for Robust Graph Neural Networks. In KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Virtual Event, CA, USA, August 23--27, 2020. 66--74."},{"key":"e_1_3_2_2_17_1","volume-title":"Self-Attentive Sequential Recommendation. In IEEE International Conference on Data Mining, ICDM 2018","author":"Kang Wang-Cheng","year":"2018","unstructured":"Wang-Cheng Kang and Julian J. McAuley. 2018. Self-Attentive Sequential Recommendation. In IEEE International Conference on Data Mining, ICDM 2018, Singapore, November 17--20, 2018. IEEE Computer Society, 197--206."},{"key":"e_1_3_2_2_18_1","volume-title":"MELT: Mutual Enhancement of Long-Tailed User and Item for Sequential Recommendation. In SIGIR. ACM, 68--77.","author":"Kim Kibum","year":"2023","unstructured":"Kibum Kim, Dongmin Hyun, Sukwon Yun, and Chanyoung Park. 2023. MELT: Mutual Enhancement of Long-Tailed User and Item for Sequential Recommendation. In SIGIR. ACM, 68--77."},{"key":"e_1_3_2_2_19_1","volume-title":"Adam: A Method for Stochastic Optimization. In 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7--9, 2015, Conference Track Proceedings.","author":"Diederik","unstructured":"Diederik P. Kingma and Jimmy Ba. 2015. Adam: A Method for Stochastic Optimization. In 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7--9, 2015, Conference Track Proceedings."},{"key":"e_1_3_2_2_20_1","volume-title":"Auto-Encoding Variational Bayes. In 2nd International Conference on Learning Representations, ICLR 2014, Banff, AB, Canada, April 14--16, 2014, Conference Track Proceedings.","author":"Diederik","unstructured":"Diederik P. Kingma and Max Welling. 2014. Auto-Encoding Variational Bayes. In 2nd International Conference on Learning Representations, ICLR 2014, Banff, AB, Canada, April 14--16, 2014, Conference Track Proceedings."},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/651"},{"key":"e_1_3_2_2_22_1","volume-title":"A Survey on Data-Centric Recommender Systems. arXiv preprint arXiv:2401.17878","author":"Lai Riwei","year":"2024","unstructured":"Riwei Lai, Li Chen, Rui Chen, and Chi Zhang. 2024. A Survey on Data-Centric Recommender Systems. arXiv preprint arXiv:2401.17878 (2024)."},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/3132847.3132926"},{"key":"e_1_3_2_2_24_1","volume-title":"Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2023","author":"Li Jiacheng","year":"2023","unstructured":"Jiacheng Li, Ming Wang, Jin Li, Jinmiao Fu, Xin Shen, Jingbo Shang, and Julian J. McAuley. 2023. Text Is All You Need: Learning Language Representations for Sequential Recommendation. In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2023, Long Beach, CA, USA, August 6--10, 2023. ACM, 1258--1267."},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"crossref","unstructured":"Defu Lian Xu Huang Xiaolong Chen Jin Chen Xingmei Wang Yankai Wang Haoran Jin Rui Fan Zheng Liu Le Wu and Enhong Chen. 2023. RecStudio: Towards a Highly-Modularized Recommender System. In SIGIR. ACM 2890-- 2900.","DOI":"10.1145\/3539618.3591894"},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"crossref","unstructured":"Weilin Lin Xiangyu Zhao Yejing Wang Yuanshao Zhu and Wanyu Wang. 2023. AutoDenoise: Automatic Data Instance Denoising for Recommendations. In WWW. ACM 1003--1011.","DOI":"10.1145\/3543507.3583339"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"crossref","unstructured":"Chong Liu Xiaoyang Liu Rongqin Zheng Lixin Zhang Xiaobo Liang Juntao Li Lijun Wu Min Zhang and Leyu Lin. 2023. CT4Rec: Simple yet Effective Consistency Training for Sequential Recommendation. In KDD. ACM 3901-- 3913.","DOI":"10.1145\/3580305.3599798"},{"key":"e_1_3_2_2_28_1","volume-title":"Privacy-Preserving Synthetic Data Generation for Recommendation Systems. In SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval","author":"Liu Fan","year":"2022","unstructured":"Fan Liu, Zhiyong Cheng, Huilin Chen, Yinwei Wei, Liqiang Nie, and Mohan S. Kankanhalli. 2022. Privacy-Preserving Synthetic Data Generation for Recommendation Systems. In SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11 - 15, 2022. 1379--1389."},{"key":"e_1_3_2_2_29_1","volume-title":"Towards Unsupervised Deep Graph Structure Learning. In WWW '22: The ACM Web Conference 2022","author":"Liu Yixin","year":"2022","unstructured":"Yixin Liu, Yu Zheng, Daokun Zhang, Hongxu Chen, Hao Peng, and Shirui Pan. 2022. Towards Unsupervised Deep Graph Structure Learning. In WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25 - 29, 2022. 1392--1403."},{"key":"e_1_3_2_2_30_1","volume-title":"SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval","author":"Liu Zhiwei","year":"2021","unstructured":"Zhiwei Liu, Ziwei Fan, Yu Wang, and Philip S. Yu. 2021. Augmenting Sequential Recommendation with Pseudo-Prior Items via Reversely Pre-training Transformer. In SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event, Canada, July 11--15, 2021. 1608--1612."},{"key":"e_1_3_2_2_31_1","volume-title":"The 23rd International Conference on Artificial Intelligence and Statistics, AISTATS 2020, 26--28","author":"Lorraine Jonathan","year":"2020","unstructured":"Jonathan Lorraine, Paul Vicol, and David Duvenaud. 2020. Optimizing Millions of Hyperparameters by Implicit Differentiation. In The 23rd International Conference on Artificial Intelligence and Statistics, AISTATS 2020, 26--28 August 2020, Online"},{"key":"e_1_3_2_2_32_1","unstructured":". 1540--1552."},{"key":"e_1_3_2_2_33_1","volume-title":"9th International Conference on Learning Representations, ICLR 2021","author":"Navon Aviv","year":"2021","unstructured":"Aviv Navon, Idan Achituve, Haggai Maron, Gal Chechik, and Ethan Fetaya. 2021. Auxiliary Learning by Implicit Differentiation. In 9th International Conference on Learning Representations, ICLR 2021, Virtual Event, Austria, May 3--7, 2021."},{"key":"e_1_3_2_2_34_1","volume-title":"Petrov and Craig Macdonald","author":"Aleksandr","year":"2022","unstructured":"Aleksandr V. Petrov and Craig Macdonald. 2022. Effective and Efficient Training for Sequential Recommendation using Recency Sampling. In RecSys. ACM, 81--91."},{"key":"e_1_3_2_2_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462836"},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"publisher","DOI":"10.1145\/3488560.3498433"},{"key":"e_1_3_2_2_37_1","volume-title":"Infinite Recommendation Networks: A Data-Centric Approach. In Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022","author":"Sachdeva Noveen","year":"2022","unstructured":"Noveen Sachdeva, Mehak Preet Dhaliwal, Carole-JeanWu, and Julian J. McAuley. 2022. Infinite Recommendation Networks: A Data-Centric Approach. In Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, NeurIPS 2022, New Orleans, LA, USA, November 28 - December 9, 2022."},{"key":"e_1_3_2_2_38_1","volume-title":"Derek Zhiyuan Cheng, and Julian J. McAuley","author":"Sachdeva Noveen","year":"2023","unstructured":"Noveen Sachdeva, Zexue He, Wang-Cheng Kang, Jianmo Ni, Derek Zhiyuan Cheng, and Julian J. McAuley. 2023. Farzi Data: Autoregressive Data Distillation. CoRR abs\/2310.09983 (2023)."},{"key":"e_1_3_2_2_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3357895"},{"key":"e_1_3_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3159652.3159656"},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/220"},{"key":"e_1_3_2_2_42_1","volume-title":"Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017","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 30: Annual Conference on Neural Information Processing Systems 2017, December 4--9, 2017, Long Beach, CA, USA. 5998--6008."},{"key":"e_1_3_2_2_43_1","doi-asserted-by":"publisher","DOI":"10.1145\/3604915.3608769"},{"key":"e_1_3_2_2_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/3463913"},{"key":"e_1_3_2_2_45_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330931"},{"key":"e_1_3_2_2_46_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2024.3354420"},{"key":"e_1_3_2_2_47_1","volume-title":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, IJCAI 2019","author":"Wang Shoujin","year":"2019","unstructured":"Shoujin Wang, Liang Hu, Yan Wang, Longbing Cao, Quan Z. Sheng, and Mehmet A. Orgun. 2019. Sequential Recommender Systems: Challenges, Progress and Prospects. In Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, IJCAI 2019, Macao, China, August 10--16, 2019. 6332--6338."},{"key":"e_1_3_2_2_48_1","volume-title":"Applications and Opportunities. In SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval","author":"Zhang Qi","year":"2022","unstructured":"ShoujinWang, Qi Zhang, Liang Hu, Xiuzhen Zhang, YanWang, and Charu Aggarwal. 2022. Sequential\/Session-based Recommendations: Challenges, Approaches, Applications and Opportunities. In SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11 - 15, 2022. ACM, 3425--3428."},{"key":"e_1_3_2_2_49_1","volume-title":"Efros","author":"Wang Tongzhou","year":"2018","unstructured":"Tongzhou Wang, Jun-Yan Zhu, Antonio Torralba, and Alexei A. Efros. 2018. Dataset Distillation. CoRR abs\/1811.10959 (2018)."},{"key":"e_1_3_2_2_50_1","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","volume":"36","author":"Hosseininasab Amin","year":"2022","unstructured":"XinWang, Amin Hosseininasab, Pablo Colunga, Serdar Kad?o?lu, and Willem-Jan van Hoeve. 2022. Seq2Pat: Sequence-to-pattern generation for constraint-based sequential pattern mining. In Proceedings of the AAAI Conference on Artificial Intelligence, Vol. 36. 12665--12671."},{"key":"e_1_3_2_2_51_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401142"},{"key":"e_1_3_2_2_52_1","volume-title":"Dataset Condensation for Recommendation. CoRR abs\/2310.01038","author":"Wu Jiahao","year":"2023","unstructured":"Jiahao Wu, Wenqi Fan, Shengcai Liu, Qijiong Liu, Rui He, Qing Li, and Ke Tang. 2023. Dataset Condensation for Recommendation. CoRR abs\/2310.01038 (2023)."},{"key":"e_1_3_2_2_53_1","volume-title":"Xiao- Ming Wu, and Ke Tang","author":"Wu Jiahao","year":"2023","unstructured":"Jiahao Wu, Qijiong Liu, Hengchang Hu, Wenqi Fan, Shengcai Liu, Qing Li, Xiao- Ming Wu, and Ke Tang. 2023. Leveraging Large Language Models (LLMs) to Empower Training-Free Dataset Condensation for Content-Based Recommendation. CoRR abs\/2310.09874 (2023)."},{"key":"e_1_3_2_2_54_1","volume-title":"A Survey on Large Language Models for Recommendation. CoRR abs\/2305.19860","author":"Wu Likang","year":"2023","unstructured":"Likang Wu, Zhi Zheng, Zhaopeng Qiu, Hao Wang, Hongchao Gu, Tingjia Shen, Chuan Qin, Chen Zhu, Hengshu Zhu, Qi Liu, Hui Xiong, and Enhong Chen. 2023. A Survey on Large Language Models for Recommendation. CoRR abs\/2305.19860 (2023)."},{"key":"e_1_3_2_2_55_1","volume-title":"Session-based Recommendation with Graph Neural Networks. CoRR abs\/1811.00855","author":"Wu Shu","year":"2018","unstructured":"Shu Wu, Yuyuan Tang, Yanqiao Zhu, Liang Wang, Xing Xie, and Tieniu Tan. 2018. Session-based Recommendation with Graph Neural Networks. CoRR abs\/1811.00855 (2018)."},{"key":"e_1_3_2_2_56_1","volume-title":"Unlocking Efficiency in Large Language Model Inference: A Comprehensive Survey of Speculative Decoding. CoRR abs\/2401.07851","author":"Xia Heming","year":"2024","unstructured":"Heming Xia, Zhe Yang, Qingxiu Dong, Peiyi Wang, Yongqi Li, Tao Ge, Tianyu Liu, Wenjie Li, and Zhifang Sui. 2024. Unlocking Efficiency in Large Language Model Inference: A Comprehensive Survey of Speculative Decoding. CoRR abs\/2401.07851 (2024)."},{"key":"e_1_3_2_2_57_1","volume-title":"Contrastive Learning for Sequential Recommendation. In 38th IEEE International Conference on Data Engineering, ICDE 2022","author":"Xie Xu","year":"2022","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 38th IEEE International Conference on Data Engineering, ICDE 2022, Kuala Lumpur, Malaysia, May 9--12, 2022. IEEE, 1259--1273."},{"key":"e_1_3_2_2_58_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/547"},{"key":"e_1_3_2_2_59_1","volume-title":"Proceedings of the 28th ACM International Conference on Information and Knowledge Management, CIKM 2019","author":"Yan An","year":"2019","unstructured":"An Yan, Shuo Cheng, Wang-Cheng Kang, Mengting Wan, and Julian J. McAuley. 2019. CosRec: 2D Convolutional Neural Networks for Sequential Recommendation. In Proceedings of the 28th ACM International Conference on Information and Knowledge Management, CIKM 2019, Beijing, China, November 3--7, 2019. 2173--2176."},{"key":"e_1_3_2_2_60_1","doi-asserted-by":"publisher","DOI":"10.1145\/3581783.3611951"},{"key":"e_1_3_2_2_61_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i9.26285"},{"key":"e_1_3_2_2_62_1","doi-asserted-by":"publisher","DOI":"10.1145\/3581783.3611809"},{"key":"e_1_3_2_2_63_1","volume-title":"DASFAA 2012, Busan, South Korea, April 15--19, 2012, Proceedings, Part II. 48--64","author":"Yap Ghim-Eng","unstructured":"Ghim-Eng Yap, Xiaoli Li, and Philip S. Yu. 2012. Effective Next-Items Recommendation via Personalized Sequential Pattern Mining. In Database Systems for Advanced Applications - 17th International Conference, DASFAA 2012, Busan, South Korea, April 15--19, 2012, Proceedings, Part II. 48--64."},{"key":"e_1_3_2_2_64_1","doi-asserted-by":"publisher","DOI":"10.1145\/3583780.3614781"},{"key":"e_1_3_2_2_65_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2023.3282907"},{"key":"e_1_3_2_2_66_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2023.3323376"},{"key":"e_1_3_2_2_67_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i5.16593"},{"key":"e_1_3_2_2_68_1","volume-title":"Kwei-Herng Lai, Fan Yang, Zhimeng Jiang, Shaochen Zhong, and Xia Hu.","author":"Zha Daochen","year":"2023","unstructured":"Daochen Zha, Zaid Pervaiz Bhat, Kwei-Herng Lai, Fan Yang, Zhimeng Jiang, Shaochen Zhong, and Xia Hu. 2023. Data-centric Artificial Intelligence: A Survey. CoRR abs\/2303.10158 (2023)."},{"key":"e_1_3_2_2_69_1","volume-title":"Robust Collaborative Filtering to Popularity Distribution Shift. CoRR abs\/2310.10696","author":"Zhang An","year":"2023","unstructured":"An Zhang, Wenchang Ma, Jingnan Zheng, Xiang Wang, and Tat-Seng Chua. 2023. Robust Collaborative Filtering to Popularity Distribution Shift. CoRR abs\/2310.10696 (2023)."},{"key":"e_1_3_2_2_70_1","doi-asserted-by":"publisher","DOI":"10.1145\/3543507.3583513"},{"key":"e_1_3_2_2_71_1","volume-title":"Dataset Condensation with Distribution Matching. In IEEE\/CVF Winter Conference on Applications of Computer Vision, WACV 2023","author":"Zhao Bo","year":"2023","unstructured":"Bo Zhao and Hakan Bilen. 2023. Dataset Condensation with Distribution Matching. In IEEE\/CVF Winter Conference on Applications of Computer Vision, WACV 2023, Waikoloa, HI, USA, January 2--7, 2023. 6503--6512."},{"key":"e_1_3_2_2_72_1","volume-title":"Dataset Condensation with Gradient Matching. In 9th International Conference on Learning Representations, ICLR 2021","author":"Zhao Bo","year":"2021","unstructured":"Bo Zhao, Konda Reddy Mopuri, and Hakan Bilen. 2021. Dataset Condensation with Gradient Matching. In 9th International Conference on Learning Representations, ICLR 2021, Virtual Event, Austria, May 3--7, 2021."},{"key":"e_1_3_2_2_73_1","volume-title":"Dataset Condensation with Gradient Matching. In 9th International Conference on Learning Representations, ICLR 2021","author":"Zhao Bo","year":"2021","unstructured":"Bo Zhao, Konda Reddy Mopuri, and Hakan Bilen. 2021. Dataset Condensation with Gradient Matching. In 9th International Conference on Learning Representations, ICLR 2021, Virtual Event, Austria, May 3--7, 2021."},{"key":"e_1_3_2_2_74_1","volume-title":"Alan Wee-Chung Liew, and Shirui Pan","author":"Zheng Xin","year":"2023","unstructured":"Xin Zheng, Yixin Liu, Zhifeng Bao, Meng Fang, Xia Hu, Alan Wee-Chung Liew, and Shirui Pan. 2023. Towards Data-centric Graph Machine Learning: Review and Outlook. CoRR abs\/2309.10979 (2023)."},{"key":"e_1_3_2_2_75_1","volume-title":"Dataset Quantization. In IEEE\/CVF International Conference on Computer Vision, ICCV 2023","author":"Zhou Daquan","year":"2023","unstructured":"Daquan Zhou, KaiWang, Jianyang Gu, Xiangyu Peng, Dongze Lian, Yifan Zhang, Yang You, and Jiashi Feng. 2023. Dataset Quantization. In IEEE\/CVF International Conference on Computer Vision, ICCV 2023, Paris, France, October 1--6, 2023. 17159-- 17170."},{"key":"e_1_3_2_2_76_1","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3411954"},{"key":"e_1_3_2_2_77_1","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3512111"},{"key":"e_1_3_2_2_78_1","volume-title":"Deep Graph Structure Learning for Robust Representations: A Survey. CoRR abs\/2103.03036","author":"Zhu Yanqiao","year":"2021","unstructured":"Yanqiao Zhu, Weizhi Xu, Jinghao Zhang, Qiang Liu, Shu Wu, and Liang Wang. 2021. Deep Graph Structure Learning for Robust Representations: A Survey. CoRR abs\/2103.03036 (2021)."},{"key":"e_1_3_2_2_79_1","volume-title":"LearnDA: Learnable knowledge-guided data augmentation for event causality identification. arXiv preprint arXiv:2106.01649","author":"Zuo Xinyu","year":"2021","unstructured":"Xinyu Zuo, Pengfei Cao, Yubo Chen, Kang Liu, Jun Zhao, Weihua Peng, and Yuguang Chen. 2021. LearnDA: Learnable knowledge-guided data augmentation for event causality identification. arXiv preprint arXiv:2106.01649 (2021)."}],"event":{"name":"KDD '24: The 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Barcelona Spain","acronym":"KDD '24","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 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3637528.3671841","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3637528.3671841","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T00:04:14Z","timestamp":1750291454000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3637528.3671841"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,24]]},"references-count":79,"alternative-id":["10.1145\/3637528.3671841","10.1145\/3637528"],"URL":"https:\/\/doi.org\/10.1145\/3637528.3671841","relation":{},"subject":[],"published":{"date-parts":[[2024,8,24]]},"assertion":[{"value":"2024-08-24","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}