{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T02:28:13Z","timestamp":1783736893102,"version":"3.55.0"},"publisher-location":"New York, NY, USA","reference-count":86,"publisher":"ACM","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,10,27]]},"DOI":"10.1145\/3746027.3754977","type":"proceedings-article","created":{"date-parts":[[2025,10,25]],"date-time":"2025-10-25T05:56:43Z","timestamp":1761371803000},"page":"6007-6016","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Generating Negative Samples for Multi-Modal Recommendation"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-8800-9561","authenticated-orcid":false,"given":"Yanbiao","family":"Ji","sequence":"first","affiliation":[{"name":"Shanghai Jiao Tong University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3243-2441","authenticated-orcid":false,"given":"Dan","family":"Luo","sequence":"additional","affiliation":[{"name":"Lehigh University, Bethlehem, PA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9341-6002","authenticated-orcid":false,"given":"Chang","family":"Liu","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-0531-1120","authenticated-orcid":false,"given":"Shaokai","family":"Wu","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5613-6239","authenticated-orcid":false,"given":"Jing","family":"Tong","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1973-9529","authenticated-orcid":false,"given":"Qichen","family":"He","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7561-9789","authenticated-orcid":false,"given":"Deyi","family":"Ji","sequence":"additional","affiliation":[{"name":"Tencent, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2300-3039","authenticated-orcid":false,"given":"Hongtao","family":"Lu","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2911-1244","authenticated-orcid":false,"given":"Yue","family":"Ding","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2025,10,27]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Multimodality Invariant Learning for Multimedia-Based New Item Recommendation (SIGIR '24)","author":"Bai Haoyue","year":"2024","unstructured":"Haoyue Bai, Le Wu, Min Hou, Miaomiao Cai, Zhuangzhuang He, Yuyang Zhou, Richang Hong, and Meng Wang. 2024. Multimodality Invariant Learning for Multimedia-Based New Item Recommendation (SIGIR '24). 677--686."},{"key":"e_1_3_2_1_2_1","unstructured":"Jinze Bai Shuai Bai Shusheng Yang Shijie Wang Sinan Tan Peng Wang Junyang Lin Chang Zhou and Jingren Zhou. 2023. Qwen-VL: A Versatile Vision- Language Model for Understanding Localization Text Reading and Beyond. arXiv:2308.12966 [cs.CV]"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3450289"},{"key":"e_1_3_2_1_4_1","volume-title":"SamWalker: Social Recommendation with Informative Sampling Strategy (WWW '19)","author":"Chen Jiawei","year":"2019","unstructured":"Jiawei Chen, CanWang, Sheng Zhou, Qihao Shi, Yan Feng, and Chun Chen. 2019. SamWalker: Social Recommendation with Informative Sampling Strategy (WWW '19). 228--239."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3077136.3080797"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"crossref","unstructured":"\u00c1d\u00e1m Tibor Czapp M\u00e1ty\u00e1s Jani B\u00e1lint Domi\u00e1n and Bal\u00e1zs Hidasi. 2024. Dynamic Product Image Generation and Recommendation at Scale for Personalized Ecommerce (RecSys '24). 768--770.","DOI":"10.1145\/3640457.3688045"},{"key":"e_1_3_2_1_7_1","unstructured":"Jianfeng Deng Qingfeng Chen Debo Cheng Jiuyong Li Lin Liu and Xiaojing Du. 2024. Mitigating Dual Latent Confounding Biases in Recommender Systems. arXiv:2410.12451 [cs.IR]"},{"key":"e_1_3_2_1_8_1","volume-title":"Robust Frame-Semantic Models with Lexical Unit Trees and Negative Samples (ACL '24)","author":"Devasier Jacob","year":"2024","unstructured":"Jacob Devasier, Yogesh Gurjar, and Chengkai Li. 2024. Robust Frame-Semantic Models with Lexical Unit Trees and Negative Samples (ACL '24)."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"crossref","unstructured":"Jingtao Ding Yuhan Quan Xiangnan He Yong Li and Depeng Jin. 2019. Reinforced negative sampling for recommendation with exposure data (IJCAI'19). 99--109.","DOI":"10.24963\/ijcai.2019\/309"},{"key":"e_1_3_2_1_10_1","volume-title":"Invariant Representation Learning for Multimedia Recommendation (MM '22)","author":"Du Xiaoyu","year":"2022","unstructured":"Xiaoyu Du, Zike Wu, Fuli Feng, Xiangnan He, and Jinhui Tang. 2022. Invariant Representation Learning for Multimedia Recommendation (MM '22). 619--628."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"crossref","unstructured":"Lu Fan Jiashu Pu Rongsheng Zhang and Xiao-Ming Wu. 2023. Neighborhoodbased Hard Negative Mining for Sequential Recommendation (SIGIR'23). 2042--2046.","DOI":"10.1145\/3539618.3591995"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3639048"},{"key":"e_1_3_2_1_13_1","volume-title":"Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (Proceedings of Machine Learning Research). PMLR.","author":"Glorot Xavier","year":"2010","unstructured":"Xavier Glorot and Yoshua Bengio. 2010. Understanding the difficulty of training deep feedforward neural networks. In Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (Proceedings of Machine Learning Research). PMLR."},{"key":"e_1_3_2_1_14_1","volume-title":"Sherjil Ozair, Aaron 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 Courville, and Yoshua Bengio. 2014. Generative Adversarial Networks. arXiv:1406.2661 [stat.ML]"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2021.3130191"},{"key":"e_1_3_2_1_16_1","volume-title":"LGMRec: Local and Global Graph Learning for Multimodal Recommendation (AAAI '24)","author":"Guo Zhiqiang","year":"2024","unstructured":"Zhiqiang Guo, Jianjun Li, Guohui Li, ChaoyangWang, Si Shi, and Bin Ruan. 2024. LGMRec: Local and Global Graph Learning for Multimodal Recommendation (AAAI '24). 8454--8462."},{"key":"e_1_3_2_1_17_1","unstructured":"Ruining He and Julian McAuley. 2016. VBPR: visual Bayesian Personalized Ranking from implicit feedback (AAAI'16). 144--150."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401063"},{"key":"e_1_3_2_1_19_1","unstructured":"Xiangnan He Yang Zhang Fuli Feng Chonggang Song Lingling Yi Guohui Ling and Yongdong Zhang. 2022. Addressing Confounding Feature Issue for Causal Recommendation. ACM Trans. Inf. Syst. (2022)."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467408"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/582415.582418"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2025.3536481"},{"key":"e_1_3_2_1_23_1","unstructured":"Deyi Ji Feng Zhao Lanyun Zhu Wenwei Jin Hongtao Lu and Jieping Ye. 2024. Discrete Latent Perspective Learning for Segmentation and Detection. arXiv:2406.10475 [cs.CV] https:\/\/arxiv.org\/abs\/2406.10475"},{"key":"e_1_3_2_1_24_1","unstructured":"Deyi Ji Lanyun Zhu Siqi Gao Peng Xu Hongtao Lu Jieping Ye and Feng Zhao. 2024. Tree-of-Table: Unleashing the Power of LLMs for Enhanced Large-Scale Table Understanding. arXiv:2411.08516 [cs.CL] https:\/\/arxiv.org\/abs\/2411.08516"},{"key":"e_1_3_2_1_25_1","unstructured":"Yanbiao Ji Yue Ding Chang Liu Yuxiang Lu Xin Xin and Hongtao Lu. 2024. Topology-Aware Popularity Debiasing via Simplicial Complexes. arXiv:2411.13892 [cs.IR]"},{"key":"e_1_3_2_1_26_1","volume-title":"DiffMM: Multi-Modal Diffusion Model for Recommendation (MM '24)","author":"Jiang Yangqin","year":"2024","unstructured":"Yangqin Jiang, Lianghao Xia, Wei Wei, Da Luo, Kangyi Lin, and Chao Huang. 2024. DiffMM: Multi-Modal Diffusion Model for Recommendation (MM '24). 7591--7599."},{"key":"e_1_3_2_1_27_1","volume-title":"Sampling-decomposable generative adversarial recommender (NIPS '20). Article","author":"Jin Binbin","year":"1897","unstructured":"Binbin Jin, Defu Lian, Zheng Liu, Qi Liu, Jianhui Ma, Xing Xie, and Enhong Chen. 2020. Sampling-decomposable generative adversarial recommender (NIPS '20). Article 1897, 11 pages."},{"key":"e_1_3_2_1_28_1","volume-title":"Hard Negative Mixing for Contrastive Learning (NeurIPS '20)","author":"Kalantidis Yannis","year":"2020","unstructured":"Yannis Kalantidis, Mert Bulent Sariyildiz, Noe Pion, Philippe Weinzaepfel, and Diane Larlus. 2020. Hard Negative Mixing for Contrastive Learning (NeurIPS '20). Article 1829, 12 pages."},{"key":"e_1_3_2_1_29_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 (ICLR '15)."},{"key":"e_1_3_2_1_30_1","article-title":"Mitigating Exposure Bias in Recommender Systems-A Comparative Analysis of Discrete Choice Models","volume":"3","author":"Krause Thorsten","year":"2024","unstructured":"Thorsten Krause, Alina Deriyeva, Jan H. Beinke, Gerrit Y. Bartels, and Oliver Thomas. 2024. Mitigating Exposure Bias in Recommender Systems-A Comparative Analysis of Discrete Choice Models. ACM Trans. Recomm. Syst. 3, 2, Article 19 (Nov. 2024), 37 pages.","journal-title":"ACM Trans. Recomm. Syst."},{"key":"e_1_3_2_1_31_1","volume-title":"Disentangled Negative Sampling for Collaborative Filtering (WSDM '23)","author":"Lai Riwei","year":"2023","unstructured":"Riwei Lai, Li Chen, Yuhan Zhao, Rui Chen, and Qilong Han. 2023. Disentangled Negative Sampling for Collaborative Filtering (WSDM '23). 96--104."},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"crossref","unstructured":"Riwei Lai Rui Chen Qilong Han Chi Zhang and Li Chen. 2025. Adaptive hardness negative sampling for collaborative filtering (AAAI'24). Article 961 8 pages.","DOI":"10.1609\/aaai.v38i8.28709"},{"key":"e_1_3_2_1_33_1","unstructured":"Hongkang Li MengWang Tengfei Ma Sijia Liu ZAIXI ZHANG and Pin-Yu Chen. 2024. What Improves the Generalization of Graph Transformers? A Theoretical Dive into the Self-attention and Positional Encoding (ICML'24)."},{"key":"e_1_3_2_1_34_1","volume-title":"Multimodal Counterfactual Learning Network for Multimedia-based Recommendation (SIGIR '23)","author":"Li Shuaiyang","year":"2023","unstructured":"Shuaiyang Li, Dan Guo, Kang Liu, Richang Hong, and Feng Xue. 2023. Multimodal Counterfactual Learning Network for Multimedia-based Recommendation (SIGIR '23). 1539--1548."},{"key":"e_1_3_2_1_35_1","unstructured":"Xingchen Li Xiang Wang Xiangnan He Long Chen Jun Xiao and Tat-Seng Chua. 2020. Hierarchical Fashion Graph Network for Personalized Outfit Recommendation. arXiv:2005.12566 [cs.IR]"},{"key":"e_1_3_2_1_36_1","volume-title":"Who To Align With: Feedback-Oriented Multi-Modal Alignment in Recommendation Systems (SIGIR '24)","author":"Li Yang","year":"2024","unstructured":"Yang Li, Qi'Ao Zhao, Chen Lin, Jinsong Su, and Zhilin Zhang. 2024. Who To Align With: Feedback-Oriented Multi-Modal Alignment in Recommendation Systems (SIGIR '24). 667--676."},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/3077136.3080658"},{"key":"e_1_3_2_1_38_1","volume-title":"Concept-Aware Denoising Graph Neural Network for Micro- Video Recommendation (CIKM '21)","author":"Liu Yiyu","year":"2021","unstructured":"Yiyu Liu, Qian Liu, Yu Tian, Changping Wang, Yanan Niu, Yang Song, and Chenliang Li. 2021. Concept-Aware Denoising Graph Neural Network for Micro- Video Recommendation (CIKM '21). 1099--1108."},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"crossref","unstructured":"Haokai Ma Ruobing Xie Lei Meng Xin Chen Xu Zhang Leyu Lin and Jie Zhou. 2023. Exploring False Hard Negative Sample in Cross-Domain Recommendation (RecSys'23). 502--514.","DOI":"10.1145\/3604915.3608791"},{"key":"e_1_3_2_1_40_1","unstructured":"Haokai Ma Ruobing Xie Lei Meng Fuli Feng Xiaoyu Du Xingwu Sun Zhanhui Kang and Xiangxu Meng. 2024. Negative Sampling in Recommendation: A Survey and Future Directions. arXiv:2409.07237 [cs.IR]"},{"key":"e_1_3_2_1_41_1","volume-title":"Multimodal Conditioned Diffusion Model for Recommendation (WWW '24)","author":"Ma Haokai","year":"2024","unstructured":"Haokai Ma, Yimeng Yang, Lei Meng, Ruobing Xie, and Xiangxu Meng. 2024. Multimodal Conditioned Diffusion Model for Recommendation (WWW '24). 1733--1740."},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"crossref","unstructured":"Masoud Mansoury Bamshad Mobasher and Herke van Hoof. 2024. Mitigating Exposure Bias in Online Learning to Rank Recommendation: A Novel Reward Model for Cascading Bandits (CIKM'24). 1638--1648.","DOI":"10.1145\/3627673.3679763"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"crossref","unstructured":"Julian McAuley Christopher Targett Qinfeng Shi and Anton van den Hengel. 2015. Image-Based Recommendations on Styles and Substitutes (SIGIR '15). 43--52.","DOI":"10.1145\/2766462.2767755"},{"key":"e_1_3_2_1_44_1","volume-title":"Bi-Objective Negative Sampling for Sensitivity-Aware Search (SIGIR '24)","author":"McKechnie Jack","year":"2024","unstructured":"Jack McKechnie, Graham McDonald, and Craig Macdonald. 2024. Bi-Objective Negative Sampling for Sensitivity-Aware Search (SIGIR '24). 2296--2300."},{"key":"e_1_3_2_1_45_1","volume-title":"Diffusion-based Negative Sampling on Graphs for Link Prediction (WWW '24)","author":"Nguyen Trung-Kien","year":"2024","unstructured":"Trung-Kien Nguyen and Yuan Fang. 2024. Diffusion-based Negative Sampling on Graphs for Link Prediction (WWW '24). 948--958."},{"key":"e_1_3_2_1_46_1","unstructured":"Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury Gregory Chanan Trevor Killeen Zeming Lin Natalia Gimelshein Luca Antiga Alban Desmaison Andreas K\u00f6pf Edward Yang Zach DeVito Martin Raison Alykhan Tejani Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai and Soumith Chintala. 2019. PyTorch: an imperative style high-performance deep learning library."},{"key":"e_1_3_2_1_47_1","volume-title":"Causal inference in statistics: An overview. Statistics Surveys 3, none","author":"Pearl Judea","year":"2009","unstructured":"Judea Pearl. 2009. Causal inference in statistics: An overview. Statistics Surveys 3, none (2009), 96 -- 146."},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"crossref","unstructured":"Gustavo Penha and Claudia Hauff. 2023. Do the Findings of Document and Passage Retrieval Generalize to the Retrieval of Responses for Dialogues? (ECIR '23). 132--147.","DOI":"10.1007\/978-3-031-28241-6_9"},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"crossref","unstructured":"Thilina Chaturanga Rajapakse Andrew Yates and Maarten de Rijke. 2024. Negative Sampling Techniques for Dense Passage Retrieval in a Multilingual Setting (SIGIR '24). 575--584.","DOI":"10.1145\/3626772.3657854"},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"crossref","unstructured":"Nils Reimers and Iryna Gurevych. 2019. Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks (EMNLP '19). 3982--3992.","DOI":"10.18653\/v1\/D19-1410"},{"key":"e_1_3_2_1_51_1","doi-asserted-by":"crossref","unstructured":"Steffen Rendle and Christoph Freudenthaler. 2014. Improving pairwise learning for item recommendation from implicit feedback (WSDM '14). 273--282.","DOI":"10.1145\/2556195.2556248"},{"key":"e_1_3_2_1_52_1","volume-title":"BPR: Bayesian personalized ranking from implicit feedback (UAI '09). 452--461.","author":"Rendle Steffen","year":"2009","unstructured":"Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, and Lars Schmidt-Thieme. 2009. BPR: Bayesian personalized ranking from implicit feedback (UAI '09). 452--461."},{"key":"e_1_3_2_1_53_1","volume-title":"On the Theories Behind Hard Negative Sampling for Recommendation (WWW '23)","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 (WWW '23). 812--822."},{"key":"e_1_3_2_1_54_1","doi-asserted-by":"crossref","unstructured":"Zihua Si Xueran Han Xiao Zhang Jun Xu Yue Yin Yang Song and Ji-Rong Wen. 2022. A Model-Agnostic Causal Learning Framework for Recommendation using Search Data (WWW '22). 224--233.","DOI":"10.1145\/3485447.3511951"},{"key":"e_1_3_2_1_55_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2022.3187556"},{"key":"e_1_3_2_1_56_1","volume-title":"Understanding the Behaviour of Contrastive Loss (CVPR '21)","author":"Wang Feng","year":"2021","unstructured":"Feng Wang and Huaping Liu. 2021. Understanding the Behaviour of Contrastive Loss (CVPR '21). 2495--2504."},{"key":"e_1_3_2_1_57_1","doi-asserted-by":"publisher","DOI":"10.1145\/3077136.3080786"},{"key":"e_1_3_2_1_58_1","volume-title":"Neural Memory Streaming Recommender Networks with Adversarial Training (KDD '18)","author":"Wang Qinyong","year":"2018","unstructured":"Qinyong Wang, Hongzhi Yin, Zhiting Hu, Defu Lian, Hao Wang, and Zi Huang. 2018. Neural Memory Streaming Recommender Networks with Adversarial Training (KDD '18). 2467--2475."},{"key":"e_1_3_2_1_59_1","doi-asserted-by":"crossref","unstructured":"Tianqi Wang Lei Chen Xiaodan Zhu Younghun Lee and Jing Gao. 2023. Weighted Contrastive Learning With False Negative Control to Help Long-tailed Product Classification (ACL '23). 6930--6941.","DOI":"10.18653\/v1\/2023.acl-industry.55"},{"key":"e_1_3_2_1_60_1","volume-title":"Deconfounded Recommendation for Alleviating Bias Amplification (KDD '21)","author":"Wang Wenjie","year":"2021","unstructured":"Wenjie Wang, Fuli Feng, Xiangnan He, Xiang Wang, and Tat-Seng Chua. 2021. Deconfounded Recommendation for Alleviating Bias Amplification (KDD '21). 1717--1725."},{"key":"e_1_3_2_1_61_1","doi-asserted-by":"crossref","unstructured":"Xiang Wang Yaokun Xu Xiangnan He Yixin Cao Meng Wang and Tat-Seng Chua. 2020. Reinforced Negative Sampling over Knowledge Graph for Recommendation (WWW '20).","DOI":"10.1145\/3366423.3380098"},{"key":"e_1_3_2_1_62_1","volume-title":"Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System (KDD '21)","author":"Wei Tianxin","year":"2021","unstructured":"Tianxin Wei, Fuli Feng, Jiawei Chen, Ziwei Wu, Jinfeng Yi, and Xiangnan He. 2021. Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System (KDD '21). 1791--1800."},{"key":"e_1_3_2_1_63_1","doi-asserted-by":"crossref","unstructured":"Tianxin Wei Fuli Feng Jiawei Chen Ziwei Wu Jinfeng Yi and Xiangnan He. 2021. Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System (KDD'21). 1791--1800.","DOI":"10.1145\/3447548.3467289"},{"key":"e_1_3_2_1_64_1","volume-title":"Graph-Refined Convolutional Network for Multimedia Recommendation with Implicit Feedback (MM '20)","author":"Wei Yinwei","year":"2020","unstructured":"Yinwei Wei, Xiang Wang, Liqiang Nie, Xiangnan He, and Tat-Seng Chua. 2020. Graph-Refined Convolutional Network for Multimedia Recommendation with Implicit Feedback (MM '20). 3541--3549."},{"key":"e_1_3_2_1_65_1","volume-title":"MMGCN: Multi-modal Graph Convolution Network for Personalized Recommendation of Micro-video (MM '19)","author":"Nie Liqiang","year":"2019","unstructured":"YinweiWei, XiangWang, Liqiang Nie, Xiangnan He, Richang Hong, and Tat-Seng Chua. 2019. MMGCN: Multi-modal Graph Convolution Network for Personalized Recommendation of Micro-video (MM '19). 1437--1445."},{"key":"e_1_3_2_1_66_1","unstructured":"Mike Wu Milan Mosse Chengxu Zhuang Daniel Yamins and Noah Goodman. 2021. Conditional Negative Sampling for Contrastive Learning of Visual Representations (ICLR'21)."},{"key":"e_1_3_2_1_67_1","volume-title":"RE-SORT: Removing Spurious Correlation in Multilevel Interaction for CTR Prediction. In The 40th Conference on Uncertainty in Artificial Intelligence (UAI'24)","author":"Wu Songli","year":"2024","unstructured":"Songli Wu, Liang Du, Jia-Qi Yang, Yuai Wang, De-Chuan Zhan, SHUANG ZHAO, and Zixun Sun. 2024. RE-SORT: Removing Spurious Correlation in Multilevel Interaction for CTR Prediction. In The 40th Conference on Uncertainty in Artificial Intelligence (UAI'24). Article 178, 13 pages."},{"key":"e_1_3_2_1_68_1","article-title":"Causal Structure Learning for Recommender System","volume":"3","author":"Xu Shuyuan","year":"2024","unstructured":"Shuyuan Xu, Da Xu, Evren Korpeoglu, Sushant Kumar, Stephen Guo, Kannan Achan, and Yongfeng Zhang. 2024. Causal Structure Learning for Recommender System. ACM Trans. Recomm. Syst. 3, 1, Article 8 (Oct. 2024), 23 pages.","journal-title":"ACM Trans. Recomm. Syst."},{"key":"e_1_3_2_1_69_1","doi-asserted-by":"publisher","DOI":"10.1145\/3474085.3475514"},{"key":"e_1_3_2_1_70_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2024.3371473"},{"key":"e_1_3_2_1_71_1","unstructured":"Yuan Yao Tianyu Yu Ao Zhang and et al. 2024. MiniCPM-V: A GPT-4V Level MLLM on Your Phone. arXiv:2408.01800 [cs.CV]"},{"key":"e_1_3_2_1_72_1","volume-title":"Graph Convolutional Neural Networks for Web-Scale Recommender Systems (KDD '18)","author":"Ying Rex","year":"2018","unstructured":"Rex Ying, Ruining He, Kaifeng Chen, Pong Eksombatchai, William L. Hamilton, and Jure Leskovec. 2018. Graph Convolutional Neural Networks for Web-Scale Recommender Systems (KDD '18). 974--983."},{"key":"e_1_3_2_1_73_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2023.3282907"},{"key":"e_1_3_2_1_74_1","volume-title":"Contrasting Intra-Modal and Ranking Cross-Modal Hard Negatives to Enhance Visio-Linguistic Finegrained Understanding. arXiv preprint arXiv:2306.08832","author":"Zhang Le","year":"2023","unstructured":"Le Zhang, Rabiul Awal, and Aishwarya Agrawal. 2023. Contrasting Intra-Modal and Ranking Cross-Modal Hard Negatives to Enhance Visio-Linguistic Finegrained Understanding. arXiv preprint arXiv:2306.08832 (2023)."},{"key":"e_1_3_2_1_75_1","volume-title":"Li","author":"Zhang Shifeng","year":"2020","unstructured":"Shifeng Zhang, Cheng Chi, Yongqiang Yao, Zhen Lei, and Stan Z. Li. 2020. Bridging the Gap Between Anchor-Based and Anchor-Free Detection via Adaptive Training Sample Selection (CVPR '20). 9756--9765."},{"key":"e_1_3_2_1_76_1","doi-asserted-by":"crossref","unstructured":"Weinan Zhang Tianqi Chen Jun Wang and Yong Yu. 2013. Optimizing top-n collaborative filtering via dynamic negative item sampling (SIGIR '13). 785--788.","DOI":"10.1145\/2484028.2484126"},{"key":"e_1_3_2_1_77_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i10.21428"},{"key":"e_1_3_2_1_78_1","doi-asserted-by":"crossref","unstructured":"Tong Zhao Julian McAuley and Irwin King. 2014. Leveraging Social Connections to Improve Personalized Ranking for Collaborative Filtering (CIKM '14). 261--270.","DOI":"10.1145\/2661829.2661998"},{"key":"e_1_3_2_1_79_1","volume-title":"Disentangling Long and Short-Term Interests for Recommendation (WWW '22)","author":"Zheng Yu","year":"2022","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 (WWW '22). 2256--2267."},{"key":"e_1_3_2_1_80_1","volume-title":"Enhancing Dyadic Relations with Homogeneous Graphs for Multimodal Recommendation. ArXiv abs\/2301.12097","author":"Zhou Hongyu","year":"2023","unstructured":"Hongyu Zhou, Xin Zhou, and Zhiqi Shen. 2023. Enhancing Dyadic Relations with Homogeneous Graphs for Multimodal Recommendation. ArXiv abs\/2301.12097 (2023)."},{"key":"e_1_3_2_1_81_1","doi-asserted-by":"crossref","unstructured":"Xin Zhou and Zhiqi Shen. 2023. A Tale of Two Graphs: Freezing and Denoising Graph Structures for Multimodal Recommendation (MM '23). 935--943.","DOI":"10.1145\/3581783.3611943"},{"key":"e_1_3_2_1_82_1","volume-title":"Bootstrap Latent Representations for Multimodal Recommendation (WWW '23)","author":"Zhou Xin","year":"2023","unstructured":"Xin Zhou, Hongyu Zhou, Yong Liu, Zhiwei Zeng, Chunyan Miao, PengweiWang, Yuan You, and Feijun Jiang. 2023. Bootstrap Latent Representations for Multimodal Recommendation (WWW '23). 845--854."},{"key":"e_1_3_2_1_83_1","volume-title":"Bootstrap Latent Representations for Multi- Modal Recommendation (WWW '23)","author":"Zhou Xin","year":"2023","unstructured":"Xin Zhou, Hongyu Zhou, Yong Liu, Zhiwei Zeng, Chunyan Miao, PengweiWang, Yuan You, and Feijun Jiang. 2023. Bootstrap Latent Representations for Multi- Modal Recommendation (WWW '23). 845--854."},{"key":"e_1_3_2_1_84_1","volume-title":"CPCF: A Cross-Prompt Contrastive Framework for Referring Multimodal Large Language Models. In Forty-second International Conference on Machine Learning. https:\/\/openreview.net\/forum?id=0MpGi6IwZr","author":"Zhu Lanyun","year":"2025","unstructured":"Lanyun Zhu, Deyi Ji, Tianrun Chen, HaiyangWu, DeWen Soh, and Jun Liu. 2025. CPCF: A Cross-Prompt Contrastive Framework for Referring Multimodal Large Language Models. In Forty-second International Conference on Machine Learning. https:\/\/openreview.net\/forum?id=0MpGi6IwZr"},{"key":"e_1_3_2_1_85_1","volume-title":"Popularity Bias in Dynamic Recommendation (KDD '21)","author":"Zhu Ziwei","year":"2021","unstructured":"Ziwei Zhu, Yun He, Xing Zhao, and James Caverlee. 2021. Popularity Bias in Dynamic Recommendation (KDD '21). 2439--2449."},{"key":"e_1_3_2_1_86_1","unstructured":"Daoming Zong Chaoyue Ding Baoxiang Li Jiakui Li and Ken Zheng. 2024. Balancing Multimodal Learning via Online Logit Modulation. 5753--5761."}],"event":{"name":"MM '25: The 33rd ACM International Conference on Multimedia","location":"Dublin Ireland","acronym":"MM '25","sponsor":["SIGMM ACM Special Interest Group on Multimedia"]},"container-title":["Proceedings of the 33rd ACM International Conference on Multimedia"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3746027.3754977","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,10]],"date-time":"2025-12-10T04:02:36Z","timestamp":1765339356000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3746027.3754977"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,27]]},"references-count":86,"alternative-id":["10.1145\/3746027.3754977","10.1145\/3746027"],"URL":"https:\/\/doi.org\/10.1145\/3746027.3754977","relation":{},"subject":[],"published":{"date-parts":[[2025,10,27]]},"assertion":[{"value":"2025-10-27","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}