{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,16]],"date-time":"2025-12-16T12:45:59Z","timestamp":1765889159284,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":70,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,8,4]],"date-time":"2023-08-04T00:00:00Z","timestamp":1691107200000},"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":[[2023,8,6]]},"DOI":"10.1145\/3580305.3599785","type":"proceedings-article","created":{"date-parts":[[2023,8,4]],"date-time":"2023-08-04T18:13:58Z","timestamp":1691172838000},"page":"5728-5738","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["ReLoop2: Building Self-Adaptive Recommendation Models via Responsive Error Compensation Loop"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5666-8320","authenticated-orcid":false,"given":"Jieming","family":"Zhu","sequence":"first","affiliation":[{"name":"Huawei Noah's Ark Lab, Shenzhen, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9000-857X","authenticated-orcid":false,"given":"Guohao","family":"Cai","sequence":"additional","affiliation":[{"name":"Huawei Noah's Ark Lab, Shenzhen, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5637-0735","authenticated-orcid":false,"given":"Junjie","family":"Huang","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2231-4663","authenticated-orcid":false,"given":"Zhenhua","family":"Dong","sequence":"additional","affiliation":[{"name":"Huawei Noah's Ark Lab, Shenzhen, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9224-2431","authenticated-orcid":false,"given":"Ruiming","family":"Tang","sequence":"additional","affiliation":[{"name":"Huawei Noah's Ark Lab, Shenzhen, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0127-2425","authenticated-orcid":false,"given":"Weinan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University, Shenzhen, China"}]}],"member":"320","published-online":{"date-parts":[[2023,8,4]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"The Tenth International Conference on Learning Representations (ICLR).","author":"Arani Elahe","year":"2022","unstructured":"Elahe Arani , Fahad Sarfraz , and Bahram Zonooz . 2022 . Learning Fast, Learning Slow: A General Continual Learning Method based on Complementary Learning System . In The Tenth International Conference on Learning Representations (ICLR). Elahe Arani, Fahad Sarfraz, and Bahram Zonooz. 2022. Learning Fast, Learning Slow: A General Continual Learning Method based on Complementary Learning System. In The Tenth International Conference on Learning Representations (ICLR)."},{"key":"e_1_3_2_1_2_1","volume-title":"Retrieval-Augmented Diffusion Models. In Annual Conference on Neural Information Processing Systems (NeurIPS).","author":"Blattmann Andreas","year":"2022","unstructured":"Andreas Blattmann , Robin Rombach , Kaan Oktay , Jonas M\u00fcller , and Bj\u00f6rn Ommer . 2022 . Retrieval-Augmented Diffusion Models. In Annual Conference on Neural Information Processing Systems (NeurIPS). Andreas Blattmann, Robin Rombach, Kaan Oktay, Jonas M\u00fcller, and Bj\u00f6rn Ommer. 2022. Retrieval-Augmented Diffusion Models. In Annual Conference on Neural Information Processing Systems (NeurIPS)."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3531922"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/509907.509965"},{"volume-title":"Behavior Sequence Transformer for E-commerce Recommendation in Alibaba. CoRR","author":"Chen Qiwei","key":"e_1_3_2_1_5_1","unstructured":"Qiwei Chen , Huan Zhao , Wei Li , Pipei Huang , and Wenwu Ou. 2019. Behavior Sequence Transformer for E-commerce Recommendation in Alibaba. CoRR , Vol. abs\/ 1905 .06874. Qiwei Chen, Huan Zhao, Wei Li, Pipei Huang, and Wenwu Ou. 2019. Behavior Sequence Transformer for E-commerce Recommendation in Alibaba. CoRR, Vol. abs\/1905.06874."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3240508.3240617"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/2988450.2988454"},{"key":"e_1_3_2_1_8_1","volume-title":"Sub-linear RACE Sketches for Approximate Kernel Density Estimation on Streaming Data. In The Web Conference 2020 (WWW). 1739--1749","author":"Coleman Benjamin","year":"2020","unstructured":"Benjamin Coleman and Anshumali Shrivastava . 2020 . Sub-linear RACE Sketches for Approximate Kernel Density Estimation on Streaming Data. In The Web Conference 2020 (WWW). 1739--1749 . Benjamin Coleman and Anshumali Shrivastava. 2020. Sub-linear RACE Sketches for Approximate Kernel Density Estimation on Streaming Data. In The Web Conference 2020 (WWW). 1739--1749."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.5555\/645925.671516"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/227683.227684"},{"volume-title":"The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR). 1423--1433.","author":"Guan Renchu","key":"e_1_3_2_1_11_1","unstructured":"Renchu Guan , Haoyu Pang , Fausto Giunchiglia , Ximing Li , Xuefeng Yang , and Xiaoyue Feng . 2022. Deployable and Continuable Meta-learning-Based Recommender System with Fast User-Incremental Updates . In The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR). 1423--1433. Renchu Guan, Haoyu Pang, Fausto Giunchiglia, Ximing Li, Xuefeng Yang, and Xiaoyue Feng. 2022. Deployable and Continuable Meta-learning-Based Recommender System with Fast User-Incremental Updates. In The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR). 1423--1433."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/239"},{"key":"e_1_3_2_1_13_1","volume-title":"Proceedings of the 37th International Conference on Machine Learning (ICML)","volume":"119","author":"Guo Ruiqi","year":"2020","unstructured":"Ruiqi Guo , Philip Sun , Erik Lindgren , Quan Geng , David Simcha , Felix Chern , and Sanjiv Kumar . 2020 . Accelerating Large-Scale Inference with Anisotropic Vector Quantization . In Proceedings of the 37th International Conference on Machine Learning (ICML) , Vol. 119 . 3887--3896. Ruiqi Guo, Philip Sun, Erik Lindgren, Quan Geng, David Simcha, Felix Chern, and Sanjiv Kumar. 2020. Accelerating Large-Scale Inference with Anisotropic Vector Quantization. In Proceedings of the 37th International Conference on Machine Learning (ICML), Vol. 119. 3887--3896."},{"key":"e_1_3_2_1_14_1","volume-title":"Proceedings of the 37th International Conference on Machine Learning (ICML) (Proceedings of Machine Learning Research","volume":"3938","author":"Guu Kelvin","year":"2020","unstructured":"Kelvin Guu , Kenton Lee , Zora Tung , Panupong Pasupat , and Ming-Wei Chang . 2020 . Retrieval Augmented Language Model Pre-Training . In Proceedings of the 37th International Conference on Machine Learning (ICML) (Proceedings of Machine Learning Research , Vol. 119). 3929-- 3938 . Kelvin Guu, Kenton Lee, Zora Tung, Panupong Pasupat, and Ming-Wei Chang. 2020. Retrieval Augmented Language Model Pre-Training. In Proceedings of the 37th International Conference on Machine Learning (ICML) (Proceedings of Machine Learning Research, Vol. 119). 3929--3938."},{"key":"e_1_3_2_1_15_1","volume-title":"Incremental Learning in Online Scenario. In 2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 13923--13932","author":"He Jiangpeng","year":"2020","unstructured":"Jiangpeng He , Runyu Mao , Zeman Shao , and Fengqing Zhu . 2020 . Incremental Learning in Online Scenario. In 2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 13923--13932 . Jiangpeng He, Runyu Mao, Zeman Shao, and Fengqing Zhu. 2020. Incremental Learning in Online Scenario. In 2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 13923--13932."},{"volume-title":"Proceedings of the 25th International Conference on World Wide Web (WWW). 507--517","author":"He Ruining","key":"e_1_3_2_1_16_1","unstructured":"Ruining He and Julian J . McAuley. 2016. Ups and Downs: Modeling the Visual Evolution of Fashion Trends with One-Class Collaborative Filtering . In Proceedings of the 25th International Conference on World Wide Web (WWW). 507--517 . Ruining He and Julian J. McAuley. 2016. Ups and Downs: Modeling the Visual Evolution of Fashion Trends with One-Class Collaborative Filtering. In Proceedings of the 25th International Conference on World Wide Web (WWW). 507--517."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3077136.3080777"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/1148170.1148222"},{"key":"e_1_3_2_1_19_1","volume-title":"REVEAL: Retrieval-Augmented Visual-Language Pre-Training with Multi-Source Multimodal Knowledge Memory. CoRR","author":"Hu Ziniu","year":"2022","unstructured":"Ziniu Hu , Ahmet Iscen , Chen Sun , Zirui Wang , Kai-Wei Chang , Yizhou Sun , Cordelia Schmid , David A. Ross , and Alireza Fathi . 2022 . REVEAL: Retrieval-Augmented Visual-Language Pre-Training with Multi-Source Multimodal Knowledge Memory. CoRR , Vol. abs\/ 2212 .05221 (2022). Ziniu Hu, Ahmet Iscen, Chen Sun, Zirui Wang, Kai-Wei Chang, Yizhou Sun, Cordelia Schmid, David A. Ross, and Alireza Fathi. 2022. REVEAL: Retrieval-Augmented Visual-Language Pre-Training with Multi-Source Multimodal Knowledge Memory. CoRR, Vol. abs\/2212.05221 (2022)."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3298689.3347043"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/276698.276876"},{"key":"e_1_3_2_1_22_1","volume-title":"Improving Image Recognition by Retrieving from Web-Scale Image-Text Data. CoRR","author":"Iscen Ahmet","year":"2023","unstructured":"Ahmet Iscen , Alireza Fathi , and Cordelia Schmid . 2023. Improving Image Recognition by Retrieving from Web-Scale Image-Text Data. CoRR , Vol. abs\/ 2304 .05173 ( 2023 ). Ahmet Iscen, Alireza Fathi, and Cordelia Schmid. 2023. Improving Image Recognition by Retrieving from Web-Scale Image-Text Data. CoRR, Vol. abs\/2304.05173 (2023)."},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/TBDATA.2019.2921572"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/2959100.2959134"},{"key":"e_1_3_2_1_25_1","volume-title":"The 5th International Conference on Learning Representations (ICLR).","author":"Kaiser Lukasz","year":"2017","unstructured":"Lukasz Kaiser , Ofir Nachum , Aurko Roy , and Samy Bengio . 2017 . Learning to Remember Rare Events . In The 5th International Conference on Learning Representations (ICLR). Lukasz Kaiser, Ofir Nachum, Aurko Roy, and Samy Bengio. 2017. Learning to Remember Rare Events. In The 5th International Conference on Learning Representations (ICLR)."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3523227.3547390"},{"key":"e_1_3_2_1_27_1","volume-title":"Proceedings of the 9th International Conference on Learning Representations (ICLR).","author":"Khandelwal Urvashi","year":"2021","unstructured":"Urvashi Khandelwal , Angela Fan , Dan Jurafsky , Luke Zettlemoyer , and Mike Lewis . 2021 a. Nearest Neighbor Machine Translation . In Proceedings of the 9th International Conference on Learning Representations (ICLR). Urvashi Khandelwal, Angela Fan, Dan Jurafsky, Luke Zettlemoyer, and Mike Lewis. 2021a. Nearest Neighbor Machine Translation. In Proceedings of the 9th International Conference on Learning Representations (ICLR)."},{"key":"e_1_3_2_1_28_1","volume-title":"Nearest Neighbor Machine Translation. In 9th International Conference on Learning Representations (ICLR).","author":"Khandelwal Urvashi","year":"2021","unstructured":"Urvashi Khandelwal , Angela Fan , Dan Jurafsky , Luke Zettlemoyer , and Mike Lewis . 2021 b. Nearest Neighbor Machine Translation. In 9th International Conference on Learning Representations (ICLR). Urvashi Khandelwal, Angela Fan, Dan Jurafsky, Luke Zettlemoyer, and Mike Lewis. 2021b. Nearest Neighbor Machine Translation. In 9th International Conference on Learning Representations (ICLR)."},{"key":"e_1_3_2_1_29_1","volume-title":"Proceedings of the 8th International Conference on Learning Representations (ICLR).","author":"Khandelwal Urvashi","year":"2020","unstructured":"Urvashi Khandelwal , Omer Levy , Dan Jurafsky , Luke Zettlemoyer , and Mike Lewis . 2020 . Generalization through Memorization: Nearest Neighbor Language Models . In Proceedings of the 8th International Conference on Learning Representations (ICLR). Urvashi Khandelwal, Omer Levy, Dan Jurafsky, Luke Zettlemoyer, and Mike Lewis. 2020. Generalization through Memorization: Nearest Neighbor Language Models. In Proceedings of the 8th International Conference on Learning Representations (ICLR)."},{"key":"e_1_3_2_1_30_1","volume-title":"Complementary Learning Systems Theory Updated. Trends in Cognitive Sciences","volume":"534","author":"Kumaran Dharshan","year":"2016","unstructured":"Dharshan Kumaran , Demis Hassabis , and James L McClelland . 2016 . What Learning Systems Do Intelligent Agents Need ? Complementary Learning Systems Theory Updated. Trends in Cognitive Sciences , Vol. 20(7) (2016), 512-- 534 . Dharshan Kumaran, Demis Hassabis, and James L McClelland. 2016. What Learning Systems Do Intelligent Agents Need? Complementary Learning Systems Theory Updated. Trends in Cognitive Sciences, Vol. 20(7) (2016), 512--534."},{"key":"e_1_3_2_1_31_1","volume-title":"Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks. In Annual Conference on Neural Information Processing Systems (NeurIPS).","author":"Lewis Patrick S. H.","year":"2020","unstructured":"Patrick S. H. Lewis , Ethan Perez , Aleksandra Piktus , Fabio Petroni , Vladimir Karpukhin , Naman Goyal , Heinrich K\u00fcttler , Mike Lewis , Wen-tau Yih, Tim Rockt\u00e4schel , Sebastian Riedel , and Douwe Kiela . 2020 . Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks. In Annual Conference on Neural Information Processing Systems (NeurIPS). Patrick S. H. Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich K\u00fcttler, Mike Lewis, Wen-tau Yih, Tim Rockt\u00e4schel, Sebastian Riedel, and Douwe Kiela. 2020. Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks. In Annual Conference on Neural Information Processing Systems (NeurIPS)."},{"key":"e_1_3_2_1_32_1","volume-title":"Few-Shot Learning for New User Recommendation in Location-based Social Networks. In The Web Conference 2020 (WWW). 2472--2478","author":"Li Ruirui","year":"2020","unstructured":"Ruirui Li , Xian Wu , Xiusi Chen , and Wei Wang . 2020 . Few-Shot Learning for New User Recommendation in Location-based Social Networks. In The Web Conference 2020 (WWW). 2472--2478 . Ruirui Li, Xian Wu, Xiusi Chen, and Wei Wang. 2020. Few-Shot Learning for New User Recommendation in Location-based Social Networks. In The Web Conference 2020 (WWW). 2472--2478."},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3350950"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3357951"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3220023"},{"key":"e_1_3_2_1_36_1","volume-title":"A Comprehensive Survey on Test-Time Adaptation under Distribution Shifts. CoRR","author":"Liang Jian","year":"2023","unstructured":"Jian Liang , Ran He , and Tieniu Tan . 2023. A Comprehensive Survey on Test-Time Adaptation under Distribution Shifts. CoRR , Vol. abs\/ 2303 .15361 ( 2023 ). Jian Liang, Ran He, and Tieniu Tan. 2023. A Comprehensive Survey on Test-Time Adaptation under Distribution Shifts. CoRR, Vol. abs\/2303.15361 (2023)."},{"key":"e_1_3_2_1_37_1","volume-title":"Towards Better Plasticity-Stability Trade-off in Incremental Learning: A Simple Linear Connector. In IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 89--98","author":"Lin Guoliang","year":"2022","unstructured":"Guoliang Lin , Hanlu Chu , and Hanjiang Lai . 2022 . Towards Better Plasticity-Stability Trade-off in Incremental Learning: A Simple Linear Connector. In IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 89--98 . Guoliang Lin, Hanlu Chu, and Hanjiang Lai. 2022. Towards Better Plasticity-Stability Trade-off in Incremental Learning: A Simple Linear Connector. In IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 89--98."},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313497"},{"key":"e_1_3_2_1_39_1","volume-title":"Concept Drift Adaptation for CTR Prediction in Online Advertising Systems. CoRR","author":"Liu Congcong","year":"2022","unstructured":"Congcong Liu , Yuejiang Li , Xiwei Zhao , Changping Peng , Zhangang Lin , and Jingping Shao . 2022. Concept Drift Adaptation for CTR Prediction in Online Advertising Systems. CoRR , Vol. abs\/ 2204 .05101 ( 2022 ). Congcong Liu, Yuejiang Li, Xiwei Zhao, Changping Peng, Zhangang Lin, and Jingping Shao. 2022. Concept Drift Adaptation for CTR Prediction in Online Advertising Systems. CoRR, Vol. abs\/2204.05101 (2022)."},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/2806416.2806603"},{"volume-title":"Retrieval Augmented Classification for Long-Tail Visual Recognition. In IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 6949--6959","author":"Long Alexander","key":"e_1_3_2_1_41_1","unstructured":"Alexander Long , Wei Yin , Thalaiyasingam Ajanthan , Vu Nguyen , Pulak Purkait , Ravi Garg , Alan Blair , Chunhua Shen , and Anton van den Hengel. 2022 . Retrieval Augmented Classification for Long-Tail Visual Recognition. In IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 6949--6959 . Alexander Long, Wei Yin, Thalaiyasingam Ajanthan, Vu Nguyen, Pulak Purkait, Ravi Garg, Alan Blair, Chunhua Shen, and Anton van den Hengel. 2022. Retrieval Augmented Classification for Long-Tail Visual Recognition. In IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 6949--6959."},{"key":"e_1_3_2_1_42_1","volume-title":"Efficient and robust approximate nearest neighbor search using hierarchical navigable small world graphs","author":"Malkov Yu A","year":"2018","unstructured":"Yu A Malkov and Dmitry A Yashunin . 2018. Efficient and robust approximate nearest neighbor search using hierarchical navigable small world graphs . IEEE transactions on pattern analysis and machine intelligence, Vol. 42 , 4 ( 2018 ), 824--836. Yu A Malkov and Dmitry A Yashunin. 2018. Efficient and robust approximate nearest neighbor search using hierarchical navigable small world graphs. IEEE transactions on pattern analysis and machine intelligence, Vol. 42, 4 (2018), 824--836."},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i4.25577"},{"key":"e_1_3_2_1_44_1","volume-title":"Why there are complementary learning systems in the hippocampus and neocortex: insights from the successes and failures of connectionist models of learning and memory. Psychological review","author":"McClelland James L","year":"1995","unstructured":"James L McClelland , Bruce L McNaughton , and Randall C O'Reilly . 1995. Why there are complementary learning systems in the hippocampus and neocortex: insights from the successes and failures of connectionist models of learning and memory. Psychological review , Vol. 102(3): 419 ( 1995 ). James L McClelland, Bruce L McNaughton, and Randall C O'Reilly. 1995. Why there are complementary learning systems in the hippocampus and neocortex: insights from the successes and failures of connectionist models of learning and memory. Psychological review, Vol. 102(3):419 (1995)."},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1145\/2487575.2488200"},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"crossref","unstructured":"Yuxian Meng Xiaoya Li Xiayu Zheng Fei Wu Xiaofei Sun Tianwei Zhang and Jiwei Li. 2022. Fast Nearest Neighbor Machine Translation. In Findings of the Association for Computational Linguistics (ACL). 555--565.  Yuxian Meng Xiaoya Li Xiayu Zheng Fei Wu Xiaofei Sun Tianwei Zhang and Jiwei Li. 2022. Fast Nearest Neighbor Machine Translation. In Findings of the Association for Computational Linguistics (ACL). 555--565.","DOI":"10.18653\/v1\/2022.findings-acl.47"},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1145\/3460231.3474239"},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330666"},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3412744"},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401440"},{"key":"e_1_3_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2016.0151"},{"key":"e_1_3_2_1_52_1","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331230"},{"key":"e_1_3_2_1_53_1","volume-title":"Factorization Machines. In Proceedings of the 10th IEEE International Conference on Data Mining (ICDM). 995--1000","author":"Rendle Steffen","year":"2010","unstructured":"Steffen Rendle . 2010 . Factorization Machines. In Proceedings of the 10th IEEE International Conference on Data Mining (ICDM). 995--1000 . Steffen Rendle. 2010. Factorization Machines. In Proceedings of the 10th IEEE International Conference on Data Mining (ICDM). 995--1000."},{"key":"e_1_3_2_1_54_1","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3357925"},{"key":"e_1_3_2_1_55_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449930"},{"key":"e_1_3_2_1_56_1","doi-asserted-by":"publisher","DOI":"10.1145\/3448016.3457550"},{"key":"e_1_3_2_1_57_1","volume-title":"A Comprehensive Survey of Continual Learning: Theory, Method and Application. CoRR","author":"Wang Liyuan","year":"2023","unstructured":"Liyuan Wang , Xingxing Zhang , Hang Su , and Jun Zhu . 2023. A Comprehensive Survey of Continual Learning: Theory, Method and Application. CoRR , Vol. abs\/ 2302 .00487 ( 2023 ). Liyuan Wang, Xingxing Zhang, Hang Su, and Jun Zhu. 2023. A Comprehensive Survey of Continual Learning: Theory, Method and Application. CoRR, Vol. abs\/2302.00487 (2023)."},{"key":"e_1_3_2_1_58_1","doi-asserted-by":"publisher","DOI":"10.1145\/3124749.3124754"},{"key":"e_1_3_2_1_59_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3450078"},{"key":"e_1_3_2_1_60_1","volume-title":"Faster Nearest Neighbor Machine Translation. CoRR","author":"Wang Shuhe","year":"2021","unstructured":"Shuhe Wang , Jiwei Li , Yuxian Meng , Rongbin Ouyang , Guoyin Wang , Xiaoya Li , Tianwei Zhang , and Shi Zong . 2021a. Faster Nearest Neighbor Machine Translation. CoRR , Vol. abs\/ 2112 .08152 ( 2021 ). Shuhe Wang, Jiwei Li, Yuxian Meng, Rongbin Ouyang, Guoyin Wang, Xiaoya Li, Tianwei Zhang, and Shi Zong. 2021a. Faster Nearest Neighbor Machine Translation. CoRR, Vol. abs\/2112.08152 (2021)."},{"key":"e_1_3_2_1_61_1","volume-title":"A Practical Incremental Method to Train Deep CTR Models. CoRR","author":"Wang Yichao","year":"2020","unstructured":"Yichao Wang , Huifeng Guo , Ruiming Tang , Zhirong Liu , and Xiuqiang He. 2020. A Practical Incremental Method to Train Deep CTR Models. CoRR , Vol. abs\/ 2009 .02147 ( 2020 ). Yichao Wang, Huifeng Guo, Ruiming Tang, Zhirong Liu, and Xiuqiang He. 2020. A Practical Incremental Method to Train Deep CTR Models. CoRR, Vol. abs\/2009.02147 (2020)."},{"key":"e_1_3_2_1_62_1","volume-title":"Ni","author":"Wang Yaqing","year":"2021","unstructured":"Yaqing Wang , Quanming Yao , James T. Kwok , and Lionel M . Ni . 2021 c. Generalizing from a Few Examples : A Survey on Few-shot Learning. ACM Comput. Surv ., Vol. 53 , 3 (2021), 63:1--63:34. Yaqing Wang, Quanming Yao, James T. Kwok, and Lionel M. Ni. 2021c. Generalizing from a Few Examples: A Survey on Few-shot Learning. ACM Comput. Surv., Vol. 53, 3 (2021), 63:1--63:34."},{"key":"e_1_3_2_1_63_1","volume-title":"Memory Networks. In 3rd International Conference on Learning Representations (ICLR).","author":"Weston Jason","year":"2015","unstructured":"Jason Weston , Sumit Chopra , and Antoine Bordes . 2015 . Memory Networks. In 3rd International Conference on Learning Representations (ICLR). Jason Weston, Sumit Chopra, and Antoine Bordes. 2015. Memory Networks. In 3rd International Conference on Learning Representations (ICLR)."},{"key":"e_1_3_2_1_64_1","volume-title":"Retrieval-Enhanced Machine Learning. In The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR). 2875--2886","author":"Zamani Hamed","year":"2022","unstructured":"Hamed Zamani , Fernando Diaz , Mostafa Dehghani , Donald Metzler , and Michael Bendersky . 2022 . Retrieval-Enhanced Machine Learning. In The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR). 2875--2886 . Hamed Zamani, Fernando Diaz, Mostafa Dehghani, Donald Metzler, and Michael Bendersky. 2022. Retrieval-Enhanced Machine Learning. In The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR). 2875--2886."},{"key":"e_1_3_2_1_65_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401167"},{"key":"e_1_3_2_1_66_1","volume-title":"Deep Interest Evolution Network for Click-Through Rate Prediction. CoRR","author":"Zhou Guorui","year":"2018","unstructured":"Guorui Zhou , Na Mou , Ying Fan , Qi Pi , Weijie Bian , Chang Zhou , Xiaoqiang Zhu , and Kun Gai . 2018a. Deep Interest Evolution Network for Click-Through Rate Prediction. CoRR , Vol. abs\/ 1809 .03672 ( 2018 ). Guorui Zhou, Na Mou, Ying Fan, Qi Pi, Weijie Bian, Chang Zhou, Xiaoqiang Zhu, and Kun Gai. 2018a. Deep Interest Evolution Network for Click-Through Rate Prediction. CoRR, Vol. abs\/1809.03672 (2018)."},{"key":"e_1_3_2_1_67_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219823"},{"key":"e_1_3_2_1_68_1","volume-title":"Open Benchmarking for Click-Through Rate Prediction. In The 30th ACM International Conference on Information and Knowledge Management (CIKM). 2759--2769","author":"Zhu Jieming","year":"2021","unstructured":"Jieming Zhu , Jinyang Liu , Shuai Yang , Qi Zhang , and Xiuqiang He . 2021 . Open Benchmarking for Click-Through Rate Prediction. In The 30th ACM International Conference on Information and Knowledge Management (CIKM). 2759--2769 . Jieming Zhu, Jinyang Liu, Shuai Yang, Qi Zhang, and Xiuqiang He. 2021. Open Benchmarking for Click-Through Rate Prediction. In The 30th ACM International Conference on Information and Knowledge Management (CIKM). 2759--2769."},{"key":"e_1_3_2_1_69_1","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3531723"},{"key":"e_1_3_2_1_70_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539618.3591988"}],"event":{"name":"KDD '23: The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"],"location":"Long Beach CA USA","acronym":"KDD '23"},"container-title":["Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3580305.3599785","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3580305.3599785","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T17:49:22Z","timestamp":1750182562000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3580305.3599785"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8,4]]},"references-count":70,"alternative-id":["10.1145\/3580305.3599785","10.1145\/3580305"],"URL":"https:\/\/doi.org\/10.1145\/3580305.3599785","relation":{},"subject":[],"published":{"date-parts":[[2023,8,4]]},"assertion":[{"value":"2023-08-04","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}