{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,20]],"date-time":"2025-11-20T13:07:11Z","timestamp":1763644031727,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":58,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,10,21]],"date-time":"2023-10-21T00:00:00Z","timestamp":1697846400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,10,21]]},"DOI":"10.1145\/3583780.3614852","type":"proceedings-article","created":{"date-parts":[[2023,10,21]],"date-time":"2023-10-21T07:45:26Z","timestamp":1697874326000},"page":"1939-1948","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Dual-Oriented Contrast for Recommendation with A Stop-Gradient Operation"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6273-3184","authenticated-orcid":false,"given":"Byungkook","family":"Oh","sequence":"first","affiliation":[{"name":"Samsung Research, Seoul, Republic of Korea"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-9305-9278","authenticated-orcid":false,"given":"Yul","family":"Kim","sequence":"additional","affiliation":[{"name":"Samsung Research, Seoul, Republic of Korea"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-1151-7765","authenticated-orcid":false,"given":"Bumky","family":"Min","sequence":"additional","affiliation":[{"name":"Samsung Research, Seoul, Republic of Korea"}]}],"member":"320","published-online":{"date-parts":[[2023,10,21]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"Jane Bromley Isabelle Guyon Yann LeCun Eduard Sackinger and Roopak Shah. 1993. Signature Verification Using a Siamese Time Delay Neural Network. In NIPS. 737--744. Jane Bromley Isabelle Guyon Yann LeCun Eduard Sackinger and Roopak Shah. 1993. Signature Verification Using a Siamese Time Delay Neural Network. In NIPS. 737--744."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/1273496.1273513"},{"key":"e_1_3_2_1_3_1","volume-title":"Julien Mairal, Piotr Bojanowski, and Armand Joulin.","author":"Caron Mathilde","year":"2021","unstructured":"Mathilde Caron , Hugo Touvron , Ishan Misra , Herv\u00e9 J\u00e9 gou , Julien Mairal, Piotr Bojanowski, and Armand Joulin. 2021 . Emerging Properties in Self-Supervised Vision Transformers. In ICCV. 9630--9640. Mathilde Caron, Hugo Touvron, Ishan Misra, Herv\u00e9 J\u00e9 gou, Julien Mairal, Piotr Bojanowski, and Armand Joulin. 2021. Emerging Properties in Self-Supervised Vision Transformers. In ICCV. 9630--9640."},{"key":"e_1_3_2_1_4_1","first-page":"1597","article-title":"A Simple Framework for Contrastive Learning of Visual Representations","volume":"119","author":"Chen Ting","year":"2020","unstructured":"Ting Chen , Simon Kornblith , Mohammad Norouzi , and Geoffrey E. Hinton . 2020 . A Simple Framework for Contrastive Learning of Visual Representations . In ICML , Vol. 119. 1597 -- 1607 . Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey E. Hinton. 2020. A Simple Framework for Contrastive Learning of Visual Representations. In ICML, Vol. 119. 1597--1607.","journal-title":"ICML"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"crossref","unstructured":"Xinlei Chen and Kaiming He. 2021. Exploring Simple Siamese Representation Learning. In CVPR. 15750--15758. Xinlei Chen and Kaiming He. 2021. Exploring Simple Siamese Representation Learning. In CVPR. 15750--15758.","DOI":"10.1109\/CVPR46437.2021.01549"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"crossref","unstructured":"Yagmur Gizem Cinar and Jean-Michel Renders. 2020. Adaptive Pointwise-Pairwise Learning-to-Rank for Content-based Personalized Recommendation. In RecSys. 414--419. Yagmur Gizem Cinar and Jean-Michel Renders. 2020. Adaptive Pointwise-Pairwise Learning-to-Rank for Content-based Personalized Recommendation. In RecSys. 414--419.","DOI":"10.1145\/3383313.3412229"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"crossref","unstructured":"Paul Covington Jay Adams and Emre Sargin. 2016. Deep Neural Networks for YouTube Recommendations. In RecSys. 191--198. Paul Covington Jay Adams and Emre Sargin. 2016. Deep Neural Networks for YouTube Recommendations. In RecSys. 191--198.","DOI":"10.1145\/2959100.2959190"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"crossref","unstructured":"Zuohui Fu Yikun Xian Ruoyuan Gao Jieyu Zhao Qiaoying Huang Yingqiang Ge Shuyuan Xu Shijie Geng Chirag Shah Yongfeng Zhang and Gerard de Melo. 2020. Fairness-Aware Explainable Recommendation over Knowledge Graphs. In SIGIR. 69--78. Zuohui Fu Yikun Xian Ruoyuan Gao Jieyu Zhao Qiaoying Huang Yingqiang Ge Shuyuan Xu Shijie Geng Chirag Shah Yongfeng Zhang and Gerard de Melo. 2020. Fairness-Aware Explainable Recommendation over Knowledge Graphs. In SIGIR. 69--78.","DOI":"10.1145\/3397271.3401051"},{"key":"e_1_3_2_1_9_1","unstructured":"Tianyu Gao Xingcheng Yao and Danqi Chen. 2021. SimCSE: Simple Contrastive Learning of Sentence Embeddings. In EMNLP. 6894--6910. Tianyu Gao Xingcheng Yao and Danqi Chen. 2021. SimCSE: Simple Contrastive Learning of Sentence Embeddings. In EMNLP. 6894--6910."},{"key":"e_1_3_2_1_10_1","first-page":"249","article-title":"Understanding the difficulty of training deep feedforward neural networks","volume":"9","author":"Glorot Xavier","year":"2010","unstructured":"Xavier Glorot and Yoshua Bengio . 2010 . Understanding the difficulty of training deep feedforward neural networks . In AISTATS , Vol. 9. 249 -- 256 . Xavier Glorot and Yoshua Bengio. 2010. Understanding the difficulty of training deep feedforward neural networks. In AISTATS, Vol. 9. 249--256.","journal-title":"AISTATS"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.5555\/2503308.2188396"},{"key":"e_1_3_2_1_12_1","unstructured":"Xiaobo Hao Yudan Liu Ruobing Xie Kaikai Ge Linyao Tang Xu Zhang and Leyu Lin. 2021. Adversarial Feature Translation for Multi-domain Recommendation. In KDD Feida Zhu Beng Chin Ooi and Chunyan Miao (Eds.). 2964--2973. Xiaobo Hao Yudan Liu Ruobing Xie Kaikai Ge Linyao Tang Xu Zhang and Leyu Lin. 2021. Adversarial Feature Translation for Multi-domain Recommendation. In KDD Feida Zhu Beng Chin Ooi and Chunyan Miao (Eds.). 2964--2973."},{"key":"e_1_3_2_1_13_1","volume-title":"Girshick","author":"He Kaiming","year":"2020","unstructured":"Kaiming He , Haoqi Fan , Yuxin Wu , Saining Xie , and Ross B . Girshick . 2020 b. Momentum Contrast for Unsupervised Visual Representation Learning. In CVPR. Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross B. Girshick. 2020b. Momentum Contrast for Unsupervised Visual Representation Learning. In CVPR."},{"key":"e_1_3_2_1_14_1","volume-title":"McAuley","author":"He Ruining","year":"2016","unstructured":"Ruining He and Julian J . McAuley . 2016 . Ups and Downs: Modeling the Visual Evolution of Fashion Trends with One-Class Collaborative Filtering. In 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 WWW. 507--517."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"crossref","unstructured":"Xiangnan He Kuan Deng Xiang Wang Yan Li Yong-Dong Zhang and Meng Wang. 2020a. LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation. In SIGIR. 639--648. Xiangnan He Kuan Deng Xiang Wang Yan Li Yong-Dong Zhang and Meng Wang. 2020a. LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation. In SIGIR. 639--648.","DOI":"10.1145\/3397271.3401063"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"crossref","unstructured":"Xiangnan He Lizi Liao Hanwang Zhang Liqiang Nie Xia Hu and Tat-Seng Chua. 2017. Neural Collaborative Filtering. In WWW. 173--182. Xiangnan He Lizi Liao Hanwang Zhang Liqiang Nie Xia Hu and Tat-Seng Chua. 2017. Neural Collaborative Filtering. In WWW. 173--182.","DOI":"10.1145\/3038912.3052569"},{"key":"e_1_3_2_1_17_1","unstructured":"R. Devon Hjelm Alex Fedorov Samuel Lavoie-Marchildon Karan Grewal Philip Bachman Adam Trischler and Yoshua Bengio. 2019. Learning deep representations by mutual information estimation and maximization. In ICLR. R. Devon Hjelm Alex Fedorov Samuel Lavoie-Marchildon Karan Grewal Philip Bachman Adam Trischler and Yoshua Bengio. 2019. Learning deep representations by mutual information estimation and maximization. In ICLR."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"crossref","unstructured":"Cheng-Kang Hsieh Longqi Yang Yin Cui Tsung-Yi Lin Serge J. Belongie and Deborah Estrin. 2017. Collaborative Metric Learning. In WWW. 193--201. Cheng-Kang Hsieh Longqi Yang Yin Cui Tsung-Yi Lin Serge J. Belongie and Deborah Estrin. 2017. Collaborative Metric Learning. In WWW. 193--201.","DOI":"10.1145\/3038912.3052639"},{"key":"e_1_3_2_1_19_1","volume-title":"Kingma and Jimmy Ba","author":"Diederik","year":"2015","unstructured":"Diederik P. Kingma and Jimmy Ba . 2015 . Adam : A Method for Stochastic Optimization. In ICLR. Diederik P. Kingma and Jimmy Ba. 2015. Adam: A Method for Stochastic Optimization. In ICLR."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2009.263"},{"key":"e_1_3_2_1_21_1","unstructured":"Dongha Lee SeongKu Kang Hyunjun Ju Chanyoung Park and Hwanjo Yu. 2021. Bootstrapping User and Item Representations for One-Class Collaborative Filtering. In SIGIR. 1513--1522. Dongha Lee SeongKu Kang Hyunjun Ju Chanyoung Park and Hwanjo Yu. 2021. Bootstrapping User and Item Representations for One-Class Collaborative Filtering. In SIGIR. 1513--1522."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"crossref","unstructured":"Shicheng Li Pengcheng Yang Fuli Luo and Jun Xie. 2021. Multi-Granularity Contrasting for Cross-Lingual Pre-Training. In ACL. 1708--1717. Shicheng Li Pengcheng Yang Fuli Luo and Jun Xie. 2021. Multi-Granularity Contrasting for Cross-Lingual Pre-Training. In ACL. 1708--1717.","DOI":"10.18653\/v1\/2021.findings-acl.149"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"crossref","unstructured":"Yan Lin Huaiyu Wan Shengnan Guo and Youfang Lin. 2021. Pre-training Context and Time Aware Location Embeddings from Spatial-Temporal Trajectories for User Next Location Prediction. In AAAI. 4241--4248. Yan Lin Huaiyu Wan Shengnan Guo and Youfang Lin. 2021. Pre-training Context and Time Aware Location Embeddings from Spatial-Temporal Trajectories for User Next Location Prediction. In AAAI. 4241--4248.","DOI":"10.1609\/aaai.v35i5.16548"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"crossref","unstructured":"Ze Liu Han Hu Yutong Lin Zhuliang Yao Zhenda Xie Yixuan Wei Jia Ning Yue Cao Zheng Zhang Li Dong Furu Wei and Baining Guo. 2022. Swin Transformer V2: Scaling Up Capacity and Resolution. In CVPR. 11999--12009. Ze Liu Han Hu Yutong Lin Zhuliang Yao Zhenda Xie Yixuan Wei Jia Ning Yue Cao Zheng Zhang Li Dong Furu Wei and Baining Guo. 2022. Swin Transformer V2: Scaling Up Capacity and Resolution. In CVPR. 11999--12009.","DOI":"10.1109\/CVPR52688.2022.01170"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"crossref","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. In CIKM. 1243--1252. 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. In CIKM. 1243--1252.","DOI":"10.1145\/3459637.3482297"},{"key":"e_1_3_2_1_26_1","unstructured":"Xiao Pan Mingxuan Wang Liwei Wu and Lei Li. 2021. Contrastive Learning for Many-to-many Multilingual Neural Machine Translation. In ACL. 244--258. Xiao Pan Mingxuan Wang Liwei Wu and Lei Li. 2021. Contrastive Learning for Many-to-many Multilingual Neural Machine Translation. In ACL. 244--258."},{"key":"e_1_3_2_1_27_1","unstructured":"P\u00e1 l Andr\u00e1 s Papp Karolis Martinkus Lukas Faber and Roger Wattenhofer. 2021. DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks. In NIPS. 21997--22009. P\u00e1 l Andr\u00e1 s Papp Karolis Martinkus Lukas Faber and Roger Wattenhofer. 2021. DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks. In NIPS. 21997--22009."},{"key":"e_1_3_2_1_28_1","volume-title":"BPR: Bayesian Personalized Ranking from Implicit Feedback. In UAI.","author":"Rendle Steffen","year":"2009","unstructured":"Steffen Rendle , Christoph Freudenthaler , Zeno Gantner , and Lars Schmidt-Thieme . 2009 . BPR: Bayesian Personalized Ranking from Implicit Feedback. In UAI. Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, and Lars Schmidt-Thieme. 2009. BPR: Bayesian Personalized Ranking from Implicit Feedback. In UAI."},{"key":"e_1_3_2_1_29_1","volume-title":"Representation Learning with Contrastive Predictive Coding. CoRR","author":"Li Yazhe","year":"2018","unstructured":"A\"a ron van den Oord, Yazhe Li , and Oriol Vinyals . 2018. Representation Learning with Contrastive Predictive Coding. CoRR , Vol. abs\/ 1807 .03748 ( 2018 ). A\"a ron van den Oord, Yazhe Li, and Oriol Vinyals. 2018. Representation Learning with Contrastive Predictive Coding. CoRR, Vol. abs\/1807.03748 (2018)."},{"key":"e_1_3_2_1_30_1","unstructured":"Petar Velickovic William Fedus William L. Hamilton Pietro Li\u00f2 Yoshua Bengio and R. Devon Hjelm. 2019. Deep Graph Infomax. In ICLR. Petar Velickovic William Fedus William L. Hamilton Pietro Li\u00f2 Yoshua Bengio and R. Devon Hjelm. 2019. Deep Graph Infomax. In ICLR."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"crossref","unstructured":"Chenyang Wang Yuanqing Yu Weizhi Ma Min Zhang Chong Chen Yiqun Liu and Shaoping Ma. 2022c. Towards Representation Alignment and Uniformity in Collaborative Filtering. In KDD. 1816--1825. Chenyang Wang Yuanqing Yu Weizhi Ma Min Zhang Chong Chen Yiqun Liu and Shaoping Ma. 2022c. Towards Representation Alignment and Uniformity in Collaborative Filtering. In KDD. 1816--1825.","DOI":"10.1145\/3534678.3539253"},{"key":"e_1_3_2_1_32_1","volume-title":"Understanding the Behaviour of Contrastive Loss. CoRR","author":"Wang Feng","year":"2020","unstructured":"Feng Wang and Huaping Liu . 2020. Understanding the Behaviour of Contrastive Loss. CoRR , Vol. abs\/ 2012 .09740 ( 2020 ). Feng Wang and Huaping Liu. 2020. Understanding the Behaviour of Contrastive Loss. CoRR, Vol. abs\/2012.09740 (2020)."},{"key":"e_1_3_2_1_33_1","volume-title":"Torr","author":"Wang Menghan","year":"2022","unstructured":"Menghan Wang , Yuchen Guo , Zhenqi Zhao , Guangzheng Hu , Yuming Shen , Mingming Gong , and Philip H. S . Torr . 2022 a. MP2: A Momentum Contrast Approach for Recommendation with Pointwise and Pairwise Learning. In SIGIR. 2105--2109. Menghan Wang, Yuchen Guo, Zhenqi Zhao, Guangzheng Hu, Yuming Shen, Mingming Gong, and Philip H. S. Torr. 2022a. MP2: A Momentum Contrast Approach for Recommendation with Pointwise and Pairwise Learning. In SIGIR. 2105--2109."},{"key":"e_1_3_2_1_34_1","first-page":"9929","article-title":"Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere","volume":"119","author":"Wang Tongzhou","year":"2020","unstructured":"Tongzhou Wang and Phillip Isola . 2020 . Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere . In ICML , Vol. 119. 9929 -- 9939 . Tongzhou Wang and Phillip Isola. 2020. Understanding Contrastive Representation Learning through Alignment and Uniformity on the Hypersphere. In ICML, Vol. 119. 9929--9939.","journal-title":"ICML"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330989"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"crossref","unstructured":"Xiang Wang Xiangnan He Meng Wang Fuli Feng and Tat-Seng Chua. 2019b. Neural Graph Collaborative Filtering. In SIGIR. 165--174. Xiang Wang Xiangnan He Meng Wang Fuli Feng and Tat-Seng Chua. 2019b. Neural Graph Collaborative Filtering. In SIGIR. 165--174.","DOI":"10.1145\/3331184.3331267"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"crossref","unstructured":"Xiting Wang Kunpeng Liu Dongjie Wang Le Wu Yanjie Fu and Xing Xie. 2022b. Multi-level Recommendation Reasoning over Knowledge Graphs with Reinforcement Learning. In WWW. 2098--2108. Xiting Wang Kunpeng Liu Dongjie Wang Le Wu Yanjie Fu and Xing Xie. 2022b. Multi-level Recommendation Reasoning over Knowledge Graphs with Reinforcement Learning. In WWW. 2098--2108.","DOI":"10.1145\/3485447.3512083"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"crossref","unstructured":"Zhenyi Wang Huan Zhao and Chuan Shi. 2022d. Profiling the Design Space for Graph Neural Networks based Collaborative Filtering. In WSDM. 1109--1119. Zhenyi Wang Huan Zhao and Chuan Shi. 2022d. Profiling the Design Space for Graph Neural Networks based Collaborative Filtering. In WSDM. 1109--1119.","DOI":"10.1145\/3488560.3498520"},{"key":"e_1_3_2_1_39_1","volume-title":"WSABIE: Scaling Up to Large Vocabulary Image Annotation. In IJCAI. 2764--2770.","author":"Weston Jason","year":"2011","unstructured":"Jason Weston , Samy Bengio , and Nicolas Usunier . 2011 . WSABIE: Scaling Up to Large Vocabulary Image Annotation. In IJCAI. 2764--2770. Jason Weston, Samy Bengio, and Nicolas Usunier. 2011. WSABIE: Scaling Up to Large Vocabulary Image Annotation. In IJCAI. 2764--2770."},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"crossref","unstructured":"Jiancan Wu Xiang Wang Fuli Feng Xiangnan He Liang Chen Jianxun Lian and Xing Xie. 2021. Self-supervised Graph Learning for Recommendation. In SIGIR. 726--735. Jiancan Wu Xiang Wang Fuli Feng Xiangnan He Liang Chen Jianxun Lian and Xing Xie. 2021. Self-supervised Graph Learning for Recommendation. In SIGIR. 726--735.","DOI":"10.1145\/3404835.3462862"},{"key":"e_1_3_2_1_41_1","volume-title":"On the Effectiveness of Sampled Softmax Loss for Item Recommendation. CoRR","author":"Wu Jiancan","year":"2022","unstructured":"Jiancan Wu , Xiang Wang , Xingyu Gao , Jiawei Chen , Hongcheng Fu , Tianyu Qiu , and Xiangnan He. 2022. On the Effectiveness of Sampled Softmax Loss for Item Recommendation. CoRR , Vol. abs\/ 2201 .02327 ( 2022 ). Jiancan Wu, Xiang Wang, Xingyu Gao, Jiawei Chen, Hongcheng Fu, Tianyu Qiu, and Xiangnan He. 2022. On the Effectiveness of Sampled Softmax Loss for Item Recommendation. CoRR, Vol. abs\/2201.02327 (2022)."},{"key":"e_1_3_2_1_42_1","unstructured":"Zhirong Wu Yuanjun Xiong Stella X. Yu and Dahua Lin. 2018. Unsupervised Feature Learning via Non-Parametric Instance Discrimination. In CVPR. Zhirong Wu Yuanjun Xiong Stella X. Yu and Dahua Lin. 2018. Unsupervised Feature Learning via Non-Parametric Instance Discrimination. In CVPR."},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1145\/1390156.1390306"},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"crossref","unstructured":"Xin Xia Hongzhi Yin Junliang Yu Qinyong Wang Lizhen Cui and Xiangliang Zhang. 2021. Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation. In AAAI. 4503--4511. Xin Xia Hongzhi Yin Junliang Yu Qinyong Wang Lizhen Cui and Xiangliang Zhang. 2021. Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation. In AAAI. 4503--4511.","DOI":"10.1609\/aaai.v35i5.16578"},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"crossref","unstructured":"Yikun Xian Zuohui Fu S. Muthukrishnan Gerard de Melo and Yongfeng Zhang. 2019. Reinforcement Knowledge Graph Reasoning for Explainable Recommendation. In SIGIR. 285--294. Yikun Xian Zuohui Fu S. Muthukrishnan Gerard de Melo and Yongfeng Zhang. 2019. Reinforcement Knowledge Graph Reasoning for Explainable Recommendation. In SIGIR. 285--294.","DOI":"10.1145\/3331184.3331203"},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"crossref","unstructured":"Ruobing Xie Qi Liu Liangdong Wang Shukai Liu Bo Zhang and Leyu Lin. 2022. Contrastive Cross-domain Recommendation in Matching. In KDD. 4226--4236. Ruobing Xie Qi Liu Liangdong Wang Shukai Liu Bo Zhang and Leyu Lin. 2022. Contrastive Cross-domain Recommendation in Matching. In KDD. 4226--4236.","DOI":"10.1145\/3534678.3539125"},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"crossref","unstructured":"Ruobing Xie Zhijie Qiu Jun Rao Yi Liu Bo Zhang and Leyu Lin. 2020. Internal and Contextual Attention Network for Cold-start Multi-channel Matching in Recommendation. In IJCAI. 2732--2738. Ruobing Xie Zhijie Qiu Jun Rao Yi Liu Bo Zhang and Leyu Lin. 2020. Internal and Contextual Attention Network for Cold-start Multi-channel Matching in Recommendation. In IJCAI. 2732--2738.","DOI":"10.24963\/ijcai.2020\/379"},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"crossref","unstructured":"Yuhao Yang Chao Huang Lianghao Xia and Chenliang Li. 2022. Knowledge Graph Contrastive Learning for Recommendation. In SIGIR. 1434--1443. Yuhao Yang Chao Huang Lianghao Xia and Chenliang Li. 2022. Knowledge Graph Contrastive Learning for Recommendation. In SIGIR. 1434--1443.","DOI":"10.1145\/3477495.3532009"},{"key":"e_1_3_2_1_49_1","volume-title":"Felix X. Yu, Ting Chen, Aditya Krishna Menon, Lichan Hong, Ed H. Chi, Steve Tjoa, Jieqi (Jay) Kang, and Evan Ettinger.","author":"Yao Tiansheng","year":"2021","unstructured":"Tiansheng Yao , Xinyang Yi , Derek Zhiyuan Cheng , Felix X. Yu, Ting Chen, Aditya Krishna Menon, Lichan Hong, Ed H. Chi, Steve Tjoa, Jieqi (Jay) Kang, and Evan Ettinger. 2021 . Self-supervised Learning for Large-scale Item Recommendations. In CIKM. 4321--4330. Tiansheng Yao, Xinyang Yi, Derek Zhiyuan Cheng, Felix X. Yu, Ting Chen, Aditya Krishna Menon, Lichan Hong, Ed H. Chi, Steve Tjoa, Jieqi (Jay) Kang, and Evan Ettinger. 2021. Self-supervised Learning for Large-scale Item Recommendations. In CIKM. 4321--4330."},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"crossref","unstructured":"Junliang Yu Hongzhi Yin Min Gao Xin Xia Xiangliang Zhang and Nguyen Quoc Viet Hung. 2021a. Socially-Aware Self-Supervised Tri-Training for Recommendation. In KDD. 2084--2092. Junliang Yu Hongzhi Yin Min Gao Xin Xia Xiangliang Zhang and Nguyen Quoc Viet Hung. 2021a. Socially-Aware Self-Supervised Tri-Training for Recommendation. In KDD. 2084--2092.","DOI":"10.1145\/3447548.3467340"},{"key":"e_1_3_2_1_51_1","volume-title":"Nguyen Quoc Viet Hung, and Xiangliang Zhang","author":"Yu Junliang","year":"2021","unstructured":"Junliang Yu , Hongzhi Yin , Jundong Li , Qinyong Wang , Nguyen Quoc Viet Hung, and Xiangliang Zhang . 2021 b. Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation. In WWW. 413--424. Junliang Yu, Hongzhi Yin, Jundong Li, Qinyong Wang, Nguyen Quoc Viet Hung, and Xiangliang Zhang. 2021b. Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation. In WWW. 413--424."},{"key":"e_1_3_2_1_52_1","doi-asserted-by":"crossref","unstructured":"Junliang Yu Hongzhi Yin Xin Xia Tong Chen Lizhen Cui and Quoc Viet Hung Nguyen. 2022. Are Graph Augmentations Necessary?: Simple Graph Contrastive Learning for Recommendation. In SIGIR. 1294--1303. Junliang Yu Hongzhi Yin Xin Xia Tong Chen Lizhen Cui and Quoc Viet Hung Nguyen. 2022. Are Graph Augmentations Necessary?: Simple Graph Contrastive Learning for Recommendation. In SIGIR. 1294--1303.","DOI":"10.1145\/3477495.3531937"},{"key":"e_1_3_2_1_53_1","doi-asserted-by":"crossref","unstructured":"Chaoning Zhang Kang Zhang Trung X. Pham Axi Niu Zhinan Qiao Chang D. Yoo and In So Kweon. 2022. Dual Temperature Helps Contrastive Learning Without Many Negative Samples: Towards Understanding and Simplifying MoCo. In CVPR. 14421--14430. Chaoning Zhang Kang Zhang Trung X. Pham Axi Niu Zhinan Qiao Chang D. Yoo and In So Kweon. 2022. Dual Temperature Helps Contrastive Learning Without Many Negative Samples: Towards Understanding and Simplifying MoCo. In CVPR. 14421--14430.","DOI":"10.1109\/CVPR52688.2022.01404"},{"key":"e_1_3_2_1_54_1","volume-title":"Jason Baldridge, Honglak Lee, and Yinfei Yang.","author":"Zhang Han","year":"2021","unstructured":"Han Zhang , Jing Yu Koh , Jason Baldridge, Honglak Lee, and Yinfei Yang. 2021 . Cross-Modal Contrastive Learning for Text-to-Image Generation. In CVPR. Han Zhang, Jing Yu Koh, Jason Baldridge, Honglak Lee, and Yinfei Yang. 2021. Cross-Modal Contrastive Learning for Text-to-Image Generation. In CVPR."},{"key":"e_1_3_2_1_55_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401169"},{"key":"e_1_3_2_1_56_1","doi-asserted-by":"crossref","unstructured":"Yu Zheng Chen Gao Jianxin Chang Yanan Niu Yang Song Depeng Jin and Yong Li. 2022. Disentangling Long and Short-Term Interests for Recommendation. In WWW. 2256--2267. Yu Zheng Chen Gao Jianxin Chang Yanan Niu Yang Song Depeng Jin and Yong Li. 2022. Disentangling Long and Short-Term Interests for Recommendation. In WWW. 2256--2267.","DOI":"10.1145\/3485447.3512098"},{"key":"e_1_3_2_1_57_1","doi-asserted-by":"crossref","unstructured":"Chang Zhou Jianxin Ma Jianwei Zhang Jingren Zhou and Hongxia Yang. 2021. Contrastive Learning for Debiased Candidate Generation in Large-Scale Recommender Systems. In KDD. 3985--3995. Chang Zhou Jianxin Ma Jianwei Zhang Jingren Zhou and Hongxia Yang. 2021. Contrastive Learning for Debiased Candidate Generation in Large-Scale Recommender Systems. In KDD. 3985--3995.","DOI":"10.1145\/3447548.3467102"},{"key":"e_1_3_2_1_58_1","volume-title":"Yutao Zhu, Sirui Wang, Fuzheng Zhang, Zhongyuan Wang, and Ji-Rong Wen.","author":"Zhou Kun","year":"2020","unstructured":"Kun Zhou , Hui Wang , Wayne Xin Zhao , Yutao Zhu, Sirui Wang, Fuzheng Zhang, Zhongyuan Wang, and Ji-Rong Wen. 2020 . S3-Rec: Self-Supervised Learning for Sequential Recommendation with Mutual Information Maximization. In CIKM. 1893--1902. Kun Zhou, Hui Wang, Wayne Xin Zhao, Yutao Zhu, Sirui Wang, Fuzheng Zhang, Zhongyuan Wang, and Ji-Rong Wen. 2020. S3-Rec: Self-Supervised Learning for Sequential Recommendation with Mutual Information Maximization. In CIKM. 1893--1902."}],"event":{"name":"CIKM '23: The 32nd ACM International Conference on Information and Knowledge Management","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web","SIGIR ACM Special Interest Group on Information Retrieval"],"location":"Birmingham United Kingdom","acronym":"CIKM '23"},"container-title":["Proceedings of the 32nd ACM International Conference on Information and Knowledge Management"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3583780.3614852","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3583780.3614852","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T16:36:57Z","timestamp":1750178217000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3583780.3614852"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,21]]},"references-count":58,"alternative-id":["10.1145\/3583780.3614852","10.1145\/3583780"],"URL":"https:\/\/doi.org\/10.1145\/3583780.3614852","relation":{},"subject":[],"published":{"date-parts":[[2023,10,21]]},"assertion":[{"value":"2023-10-21","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}