{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T17:15:31Z","timestamp":1775841331613,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":47,"publisher":"ACM","funder":[{"name":"Hong Kong Baptist University Key Research Partnership Scheme","award":["KRPS\/23-24\/02"],"award-info":[{"award-number":["KRPS\/23-24\/02"]}]},{"name":"NSFC\/RGC Joint Research Scheme","award":["N_HKBU214\/24"],"award-info":[{"award-number":["N_HKBU214\/24"]}]},{"name":"National Natural Science Foundation of China","award":["62461160311"],"award-info":[{"award-number":["62461160311"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,4,13]]},"DOI":"10.1145\/3774904.3792703","type":"proceedings-article","created":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T21:54:39Z","timestamp":1775771679000},"page":"6865-6875","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["The Double-Edged Sword of Knowledge Transfer: Diagnosing and Curing Fairness Pathologies in Cross-Domain Recommendation"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1427-4139","authenticated-orcid":false,"given":"Yuhan","family":"Zhao","sequence":"first","affiliation":[{"name":"Hong Kong Baptist University, Hong Kong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4435-4017","authenticated-orcid":false,"given":"Weixin","family":"Chen","sequence":"additional","affiliation":[{"name":"Hong Kong Baptist University, Hong Kong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5842-838X","authenticated-orcid":false,"given":"Li","family":"Chen","sequence":"additional","affiliation":[{"name":"Hong Kong Baptist University, Hong Kong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6326-9531","authenticated-orcid":false,"given":"Weike","family":"Pan","sequence":"additional","affiliation":[{"name":"Shenzhen University, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2026,4,12]]},"reference":[{"key":"e_1_3_2_1_1_1","first-page":"4764","article-title":"DDCDR","author":"An Zhicheng","year":"2024","unstructured":"Zhicheng An, Zhexu Gu, Li Yu, Ke Tu, Zhengwei Wu, Binbin Hu, Zhiqiang Zhang, Lihong Gu, and Jinjie Gu. 2024. DDCDR: A Disentangle-based Distillation Framework for Cross-Domain Recommendation. In KDD. 4764-4773.","journal-title":"A Disentangle-based Distillation Framework for Cross-Domain Recommendation. In KDD."},{"key":"e_1_3_2_1_2_1","first-page":"2212","article-title":"Fairness in Recommendation Ranking through Pairwise Comparisons","author":"Beutel Alex","year":"2019","unstructured":"Alex Beutel, Jilin Chen, Tulsee Doshi, Hai Qian, Li Wei, Yi Wu, Lukasz Heldt, Zhe Zhao, Lichan Hong, Ed H Chi, et al., 2019. Fairness in Recommendation Ranking through Pairwise Comparisons. In KDD. 2212-2220.","journal-title":"KDD."},{"key":"e_1_3_2_1_3_1","first-page":"1241","article-title":"Revisiting Approximate Metric Optimization in the Age of Deep Neural Networks","author":"Bruch Sebastian","year":"2019","unstructured":"Sebastian Bruch, Masrour Zoghi, Michael Bendersky, and Marc Najork. 2019. Revisiting Approximate Metric Optimization in the Age of Deep Neural Networks. In SIGIR. 1241-1244.","journal-title":"SIGIR."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3744240"},{"key":"e_1_3_2_1_5_1","volume-title":"TORS","volume":"4","author":"Chen Weixin","year":"2025","unstructured":"Weixin Chen, Li Chen, and Yuhan Zhao. 2025a. Investigating User-side fairness in outcome and process for multi-type sensitive attributes in recommendations. TORS, Vol. 4, 2, Article 25 (2025), 29 pages."},{"key":"e_1_3_2_1_6_1","unstructured":"Weixin Chen Li Chen and Yuhan Zhao. 2026 a. Post-Training Fairness Control: A Single-Train Framework for Dynamic Fairness in Recommendation. In WWW Companion."},{"key":"e_1_3_2_1_7_1","first-page":"226","article-title":"Leave No One Behind","author":"Chen Weixin","year":"2025","unstructured":"Weixin Chen, Yuhan Zhao, Li Chen, and Weike Pan. 2025c. Leave No One Behind: Fairness-Aware Cross-Domain Recommender Systems for Non-Overlapping Users. In RecSys. 226-236.","journal-title":"Fairness-Aware Cross-Domain Recommender Systems for Non-Overlapping Users. In RecSys."},{"key":"e_1_3_2_1_8_1","volume-title":"Tong Zhao, Neil Shah, Li Chen, and Yongfeng Zhang. 2026 b. MemRec: Collaborative Memory-Augmented Agentic Recommender System. arXiv preprint arXiv:2601.08816","author":"Chen Weixin","year":"2026","unstructured":"Weixin Chen, Yuhan Zhao, Jingyuan Huang, Zihe Ye, Clark Mingxuan Ju, Tong Zhao, Neil Shah, Li Chen, and Yongfeng Zhang. 2026 b. MemRec: Collaborative Memory-Augmented Agentic Recommender System. arXiv preprint arXiv:2601.08816 (2026)."},{"key":"e_1_3_2_1_9_1","volume-title":"NeurIPS","volume":"33","author":"Ding Jingtao","year":"2020","unstructured":"Jingtao Ding, Yuhan Quan, Quanming Yao, Yong Li, and Depeng Jin. 2020. Simplify and Robustify Negative Sampling for Implicit Collaborative Filtering. NeurIPS, Vol. 33 (2020)."},{"key":"e_1_3_2_1_10_1","first-page":"161","article-title":"Cross-Domain Recommendation via Cluster-Level Latent Factor Model","author":"Gao Sheng","year":"2013","unstructured":"Sheng Gao, Hao Luo, Da Chen, Shantao Li, Patrick Gallinari, and Jun Guo. 2013. Cross-Domain Recommendation via Cluster-Level Latent Factor Model. In PKDD. 161-176.","journal-title":"PKDD."},{"key":"e_1_3_2_1_11_1","first-page":"3139","article-title":"Prompt-Enhanced Federated Content Representation Learning for Cross-Domain Recommendation","author":"Guo Lei","year":"2024","unstructured":"Lei Guo, Ziang Lu, Junliang Yu, Quoc Viet Hung Nguyen, and Hongzhi Yin. 2024. Prompt-Enhanced Federated Content Representation Learning for Cross-Domain Recommendation. In WWW. 3139-3149.","journal-title":"WWW."},{"key":"e_1_3_2_1_12_1","first-page":"770","article-title":"Deep Residual learning for Image Recognition","author":"He Kaiming","year":"2016","unstructured":"Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016. Deep Residual learning for Image Recognition. In CVPR. 770-778.","journal-title":"CVPR."},{"key":"e_1_3_2_1_13_1","first-page":"667","article-title":"CoNet","author":"Hu Guangneng","year":"2018","unstructured":"Guangneng Hu, Yu Zhang, and Qiang Yang. 2018. CoNet: Collaborative Cross Networks for Cross-Domain Recommendation. In CIKM. 667-676.","journal-title":"Collaborative Cross Networks for Cross-Domain Recommendation. In CIKM."},{"key":"e_1_3_2_1_14_1","first-page":"665","article-title":"MixGCF","author":"Huang Tinglin","year":"2021","unstructured":"Tinglin Huang, Yuxiao Dong, Ming Ding, Zhen Yang, Wenzheng Feng, Xinyu Wang, and Jie Tang. 2021. MixGCF: An Improved Training Method for Graph Neural Network-based Recommender Systems. In KDD. 665-674.","journal-title":"In KDD."},{"key":"e_1_3_2_1_15_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."},{"key":"e_1_3_2_1_16_1","first-page":"1054","article-title":"Towards Personalized Fairness based on Causal Notion","author":"Li Yunqi","year":"2021","unstructured":"Yunqi Li, Hanxiong Chen, Shuyuan Xu, Yingqiang Ge, and Yongfeng Zhang. 2021. Towards Personalized Fairness based on Causal Notion. In SIGIR. 1054-1063.","journal-title":"SIGIR."},{"key":"e_1_3_2_1_17_1","first-page":"1541","article-title":"Towards Interest Drift-driven User Representation Learning in Sequential Recommendation","author":"Lin Xiaolin","year":"2025","unstructured":"Xiaolin Lin, Weike Pan, and Zhong Ming. 2025. Towards Interest Drift-driven User Representation Learning in Sequential Recommendation. In SIGIR. 1541-1551.","journal-title":"SIGIR."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i8.28723"},{"key":"e_1_3_2_1_19_1","first-page":"885","article-title":"Cross Domain Recommendation via Bi-Directional Transfer Graph Collaborative Filtering Networks","author":"Liu Meng","year":"2020","unstructured":"Meng Liu, Jianjun Li, Guohui Li, and Peng Pan. 2020. Cross Domain Recommendation via Bi-Directional Transfer Graph Collaborative Filtering Networks. In CIKM. 885-894.","journal-title":"CIKM."},{"key":"e_1_3_2_1_20_1","first-page":"334","article-title":"User Distribution Mapping Modelling with Collaborative Filtering for Cross Domain Recommendation","author":"Liu Weiming","year":"2024","unstructured":"Weiming Liu, Chaochao Chen, Xinting Liao, Mengling Hu, Jiajie Su, Yanchao Tan, and Fan Wang. 2024a. User Distribution Mapping Modelling with Collaborative Filtering for Cross Domain Recommendation. In WWW. 334-343.","journal-title":"WWW."},{"key":"e_1_3_2_1_21_1","first-page":"1181","article-title":"Collaborative Filtering with Attribution Alignment for Review-based Non-overlapped Cross Domain Recommendation","author":"Liu Weiming","year":"2022","unstructured":"Weiming Liu, Xiaolin Zheng, Mengling Hu, and Chaochao Chen. 2022. Collaborative Filtering with Attribution Alignment for Review-based Non-overlapped Cross Domain Recommendation. In WWW. 1181-1190.","journal-title":"WWW."},{"key":"e_1_3_2_1_22_1","first-page":"452","article-title":"BPR: Bayesian Personalized Ranking from Implicit Feedback","author":"Rendle Steffen","year":"2009","unstructured":"Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, and Schmidt-Thieme. 2009. BPR: Bayesian Personalized Ranking from Implicit Feedback. In UAI. 452-461.","journal-title":"UAI."},{"key":"e_1_3_2_1_23_1","first-page":"812","article-title":"On the Theories behind Hard Negative Sampling for Recommendation","author":"Shi Wentao","year":"2023","unstructured":"Wentao Shi, Jiawei Chen, Fuli Feng, Jizhi Zhang, Junkang Wu, Chongming Gao, and Xiangnan He. 2023. On the Theories behind Hard Negative Sampling for Recommendation. In WWW. 812-822.","journal-title":"WWW."},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1145\/1401890.1401969"},{"key":"e_1_3_2_1_25_1","first-page":"1139","article-title":"On the Importance of Initialization and Momentum in Deep Learning","author":"Sutskever Ilya","year":"2013","unstructured":"Ilya Sutskever, James Martens, George Dahl, and Geoffrey Hinton. 2013. On the Importance of Initialization and Momentum in Deep Learning. In ICML. 1139-1147.","journal-title":"ICML."},{"key":"e_1_3_2_1_26_1","first-page":"293","article-title":"Fairness-aware Cross-Domain Recommendation","author":"Tang Jiakai","year":"2024","unstructured":"Jiakai Tang, Xueyang Feng, and Xu Chen. 2024. Fairness-aware Cross-Domain Recommendation. In DASFAA. 293-302.","journal-title":"DASFAA."},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/3653448"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3690382"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3547333"},{"key":"e_1_3_2_1_30_1","first-page":"2001","article-title":"Making Non-Overlapping Matters","volume":"37","author":"Wang Zihan","year":"2025","unstructured":"Zihan Wang, Yonghui Yang, Le Wu, Richang Hong, and Meng Wang. 2025a. Making Non-Overlapping Matters: An Unsupervised Alignment Enhanced Cross-Domain Cold-Start Recommendation. TKDE, Vol. 37 (2025), 2001-2014.","journal-title":"An Unsupervised Alignment Enhanced Cross-Domain Cold-Start Recommendation. TKDE"},{"key":"e_1_3_2_1_31_1","first-page":"3261","article-title":"FairCDR","author":"Wu Yongxuan","year":"2025","unstructured":"Yongxuan Wu, Yang Liu, Xixun Lin, Hong Zhou, Yanan Cao, Lixin Zou, Yanmin Shang, and Yanbing Liu. 2025. FairCDR: Transferring Fairness and User Preferences for Cross-Domain Recommendation. In KDD. 3261-3272.","journal-title":"Transferring Fairness and User Preferences for Cross-Domain Recommendation. In KDD."},{"key":"e_1_3_2_1_32_1","first-page":"4226","article-title":"Contrastive Cross-Domain Recommendation in Matching","author":"Xie Ruobing","year":"2022","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.","journal-title":"KDD."},{"key":"e_1_3_2_1_33_1","first-page":"18056","article-title":"iAgent: LLM Agent as a Shield between User and Recommender Systems","author":"Xu Wujiang","year":"2025","unstructured":"Wujiang Xu, Yunxiao Shi, Zujie Liang, Xuying Ning, Kai Mei, Kun Wang, Xi Zhu, Min Xu, and Yongfeng Zhang. 2025b. iAgent: LLM Agent as a Shield between User and Recommender Systems. In Findings of ACL. 18056-18084.","journal-title":"Findings of ACL."},{"key":"e_1_3_2_1_34_1","first-page":"1951","article-title":"Heterogeneous Graph Transfer Learning for Category-aware Cross-Domain Sequential Recommendation","author":"Xu Zitao","year":"2025","unstructured":"Zitao Xu, Xiaoqing Chen, Weike Pan, and Zhong Ming. 2025a. Heterogeneous Graph Transfer Learning for Category-aware Cross-Domain Sequential Recommendation. In WWW. 1951-1962.","journal-title":"WWW."},{"key":"e_1_3_2_1_35_1","first-page":"3667","article-title":"Ensuring User-side Fairness in Dynamic Recommender Systems","author":"Yoo Hyunsik","year":"2024","unstructured":"Hyunsik Yoo, Zhichen Zeng, Jian Kang, Ruizhong Qiu, David Zhou, Zhining Liu, Fei Wang, Charlie Xu, Eunice Chan, and Hanghang Tong. 2024. Ensuring User-side Fairness in Dynamic Recommender Systems. In WWW. 3667-3678.","journal-title":"WWW."},{"key":"e_1_3_2_1_36_1","first-page":"11480","article-title":"Tenrec","volume":"35","author":"Yuan Guanghu","year":"2022","unstructured":"Guanghu Yuan, Fajie Yuan, Yudong Li, Beibei Kong, Shujie Li, Lei Chen, Min Yang, Chenyun Yu, Bo Hu, Zang Li, et al., 2022. Tenrec: A Large-Scale Multipurpose Benchmark Dataset for Recommender Systems. NeurIPS, Vol. 35 (2022), 11480-11493.","journal-title":"A Large-Scale Multipurpose Benchmark Dataset for Recommender Systems. NeurIPS"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/3548455"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-30672-3_11"},{"key":"e_1_3_2_1_39_1","first-page":"785","article-title":"Optimizing Top-N Collaborative Filtering via Dynamic Negative Item Sampling","author":"Zhang Weinan","year":"2013","unstructured":"Weinan Zhang, Tianqi Chen, Jun Wang, and Yong Yu. 2013. Optimizing Top-N Collaborative Filtering via Dynamic Negative Item Sampling. In SIGIR. 785-788.","journal-title":"SIGIR."},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"crossref","unstructured":"Wayne Xin Zhao Yupeng Hou Xingyu Pan Chen Yang Zeyu Zhang Zihan Lin Jingsen Zhang Shuqing Bian Jiakai Tang Wenqi Sun et al. 2022. RecBole 2.0: Towards a More Up-to-Date Recommendation Library. In CIKM. 4722-4726.","DOI":"10.1145\/3511808.3557680"},{"key":"e_1_3_2_1_41_1","first-page":"4653","article-title":"Recbole: Towards a Unified","author":"Zhao Wayne Xin","year":"2021","unstructured":"Wayne Xin Zhao, Shanlei Mu, Yupeng Hou, Zihan Lin, Yushuo Chen, Xingyu Pan, Kaiyuan Li, Yujie Lu, Hui Wang, Changxin Tian, et al., 2021. Recbole: Towards a Unified, Comprehensive and Efficient Framework for Recommendation Algorithms. In CIKM. 4653-4664.","journal-title":"Comprehensive and Efficient Framework for Recommendation Algorithms. In CIKM."},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"crossref","unstructured":"Yuhan Zhao Rui Chen Li Chen Shuang Zhang Qilong Han and Hongtao Song. 2025. From Pairwise to Ranking: Climbing the Ladder to Ideal Collaborative Filtering with Pseudo-Ranking. In AAAI. Article 1489 9 pages.","DOI":"10.1609\/aaai.v39i12.33462"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"crossref","unstructured":"Yuhan Zhao Rui Chen Qilong Han Hongtao Song and Li Chen. 2024. Unlocking the Hidden Treasures: Enhancing Recommendations with Unlabeled Data. In RecSys. 247\u2013256.","DOI":"10.1145\/3640457.3688149"},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"crossref","unstructured":"Yuhan Zhao Rui Chen Riwei Lai Qilong Han Hongtao Song and Li Chen. 2023. Augmented Negative Sampling for Collaborative Filtering. In RecSys. 256\u2013266.","DOI":"10.1145\/3604915.3608811"},{"key":"e_1_3_2_1_45_1","first-page":"1533","article-title":"Dtcdr","author":"Zhu Feng","year":"2019","unstructured":"Feng Zhu, Chaochao Chen, Yan Wang, Guanfeng Liu, and Xiaolin Zheng. 2019. Dtcdr: A Framework for Dual-Target Cross-Domain Recommendation. In CIKM. 1533-1542.","journal-title":"A Framework for Dual-Target Cross-Domain Recommendation. In CIKM."},{"key":"e_1_3_2_1_46_1","volume-title":"Cross-Domain Recommendation: Challenges, Progress, and Prospects. arXiv preprint arXiv:2103.01696","author":"Zhu Feng","year":"2021","unstructured":"Feng Zhu, Yan Wang, Chaochao Chen, Jun Zhou, Longfei Li, and Guanfeng Liu. 2021. Cross-Domain Recommendation: Challenges, Progress, and Prospects. arXiv preprint arXiv:2103.01696 (2021)."},{"key":"e_1_3_2_1_47_1","first-page":"277","article-title":"A Gain-Tuning Dynamic Negative Sampler for Recommendation","author":"Zhu Qiannan","year":"2022","unstructured":"Qiannan Zhu, Haobo Zhang, Qing He, and Zhicheng Dou. 2022. A Gain-Tuning Dynamic Negative Sampler for Recommendation. In WWW. 277-285.","journal-title":"WWW."}],"event":{"name":"WWW '26: The ACM Web Conference 2026","location":"Dubai United Arab Emirates","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web"]},"container-title":["Proceedings of the ACM Web Conference 2026"],"original-title":[],"deposited":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T16:33:52Z","timestamp":1775838832000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3774904.3792703"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,12]]},"references-count":47,"alternative-id":["10.1145\/3774904.3792703","10.1145\/3774904"],"URL":"https:\/\/doi.org\/10.1145\/3774904.3792703","relation":{},"subject":[],"published":{"date-parts":[[2026,4,12]]},"assertion":[{"value":"2026-04-12","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}