| 2024 | Leveraging Multimodal Features and Item-level User Feedback for Bundle Construction. | Yunshan Ma, Xiaohao Liu, Yinwei Wei, Zhulin Tao, Xiang Wang, Tat-Seng Chua |
| 2024 | An Interpretable Brain Graph Contrastive Learning Framework for Brain Disorder Analysis. | Xuexiong Luo, Guangwei Dong, Jia Wu, Amin Beheshti, Jian Yang, Shan Xue |
| 2024 | Attribute Simulation for Item Embedding Enhancement in Multi-interest Recommendation. | Yaokun Liu, Xiaowang Zhang, Minghui Zou, Zhiyong Feng |
| 2024 | Interact with the Explanations: Causal Debiased Explainable Recommendation System. | Xu Liu, Tong Yu, Kaige Xie, Junda Wu, Shuai Li |
| 2024 | Knowledge Graph Context-Enhanced Diversified Recommendation. | Xiaolong Liu, Liangwei Yang, Zhiwei Liu, Mingdai Yang, Chen Wang, Hao Peng, Philip S. Yu |
| 2024 | MultiFS: Automated Multi-Scenario Feature Selection in Deep Recommender Systems. | Dugang Liu, Chaohua Yang, Xing Tang, Yejing Wang, Fuyuan Lyu, Weihong Luo, Xiuqiang He, Zhong Ming, Xiangyu Zhao |
| 2024 | Capturing Temporal Node Evolution via Self-supervised Learning: A New Perspective on Dynamic Graph Learning. | Lingwen Liu, Guangqi Wen, Peng Cao, Jinzhu Yang, Weiping Li, Osmar R. Zaane |
| 2024 | Generative Models for Complex Logical Reasoning over Knowledge Graphs. | Yu Liu, Yanan Cao, Shi Wang, Qingyue Wang, Guanqun Bi |
| 2024 | ONCE: Boosting Content-based Recommendation with Both Open- and Closed-source Large Language Models. | Qijiong Liu, Nuo Chen, Tetsuya Sakai, Xiao-Ming Wu |
| 2024 | Text-Video Retrieval via Multi-Modal Hypergraph Networks. | Qian Li, Lixin Su, Jiashu Zhao, Long Xia, Hengyi Cai, Suqi Cheng, Hengzhu Tang, Junfeng Wang, Dawei Yin |
| 2024 | CDRNP: Cross-Domain Recommendation to Cold-Start Users via Neural Process. | Xiaodong Li, Jiawei Sheng, Jiangxia Cao, Wenyuan Zhang, Quangang Li, Tingwen Liu |
| 2024 | Multi-Sequence Attentive User Representation Learning for Side-information Integrated Sequential Recommendation. | Xiaolin Lin, Jinwei Luo, Junwei Pan, Weike Pan, Zhong Ming, Xun Liu, Shudong Huang, Jie Jiang |
| 2024 | Inverse Learning with Extremely Sparse Feedback for Recommendation. | Guanyu Lin, Chen Gao, Yu Zheng, Yinfeng Li, Jianxin Chang, Yanan Niu, Yang Song, Kun Gai, Zhiheng Li, Depeng Jin, Yong Li |
| 2024 | Mixed Attention Network for Cross-domain Sequential Recommendation. | Guanyu Lin, Chen Gao, Yu Zheng, Jianxin Chang, Yanan Niu, Yang Song, Kun Gai, Zhiheng Li, Depeng Jin, Yong Li, Meng Wang |
| 2024 | Pre-trained Recommender Systems: A Causal Debiasing Perspective. | Ziqian Lin, Hao Ding, Trong Nghia Hoang, Branislav Kveton, Anoop Deoras, Hao Wang |
| 2024 | Global Heterogeneous Graph and Target Interest Denoising for Multi-behavior Sequential Recommendation. | Xuewei Li, Hongwei Chen, Jian Yu, Mankun Zhao, Tianyi Xu, Wenbin Zhang, Mei Yu |
| 2024 | Multi-Intent Attribute-Aware Text Matching in Searching. | Mingzhe Li, Xiuying Chen, Jing Xiang, Qishen Zhang, Changsheng Ma, Chenchen Dai, Jinxiong Chang, Zhongyi Liu, Guannan Zhang |
| 2024 | Understanding User Behavior in Carousel Recommendation Systems for Click Modeling and Learning to Rank. | Santiago de Leon-Martinez |
| 2024 | Likelihood-Based Methods Improve Parameter Estimation in Opinion Dynamics Models. | Jacopo Lenti, Corrado Monti, Gianmarco De Francisci Morales |
| 2024 | Learning Opinion Dynamics from Data. | Jacopo Lenti |
| 2024 | Grounded and Transparent Response Generation for Conversational Information-Seeking Systems. | Weronika Lajewska |
| 2024 | WSDM 2024 Workshop on Representation Learning & Clustering. | Lazhar Labiod, Mohamed Nadif, Aghiles Salah |
| 2024 | Towards Trustworthy Large Language Models. | Sanmi Koyejo, Bo Li |
| 2024 | C²DR: Robust Cross-Domain Recommendation based on Causal Disentanglement. | Menglin Kong, Jia Wang, Yushan Pan, Haiyang Zhang, Muzhou Hou |
| 2024 | MONET: Modality-Embracing Graph Convolutional Network and Target-Aware Attention for Multimedia Recommendation. | Yungi Kim, Taeri Kim, Won-Yong Shin, Sang-Wook Kim |