| 2024 | DisCo: Towards Harmonious Disentanglement and Collaboration between Tabular and Semantic Space for Recommendation. | Kounianhua Du, Jizheng Chen, Jianghao Lin, Yunjia Xi, Hangyu Wang, Xinyi Dai, Bo Chen, Ruiming Tang, Weinan Zhang |
| 2024 | Auctions with LLM Summaries. | Avinava Dubey, Zhe Feng, Rahul Kidambi, Aranyak Mehta, Di Wang |
| 2024 | Reserving-Masking-Reconstruction Model for Self-Supervised Heterogeneous Graph Representation. | Haoran Duan, Cheng Xie, Linyu Li |
| 2024 | Pre-Training Identification of Graph Winning Tickets in Adaptive Spatial-Temporal Graph Neural Networks. | Wenying Duan, Tianxiang Fang, Hong Rao, Xiaoxi He |
| 2024 | Estimated Judge Reliabilities for Weighted Bradley-Terry-Luce Are Not Reliable. | Andrew F. Dreher, Etienne Vouga, Donald S. Fussell |
| 2024 | Unsupervised Alignment of Hypergraphs with Different Scales. | Manh Tuan Do, Kijung Shin |
| 2024 | IDEA: A Flexible Framework of Certified Unlearning for Graph Neural Networks. | Yushun Dong, Binchi Zhang, Zhenyu Lei, Na Zou, Jundong Li |
| 2024 | Heterogeneity-Informed Meta-Parameter Learning for Spatiotemporal Time Series Forecasting. | Zheng Dong, Renhe Jiang, Haotian Gao, Hangchen Liu, Jinliang Deng, Qingsong Wen, Xuan Song |
| 2024 | FNSPID: A Comprehensive Financial News Dataset in Time Series. | Zihan Dong, Xinyu Fan, Zhiyuan Peng |
| 2024 | Next-generation Intelligent Assistants for Wearable Devices. | Xin Luna Dong |
| 2024 | Enhancing On-Device LLM Inference with Historical Cloud-Based LLM Interactions. | Yucheng Ding, Chaoyue Niu, Fan Wu, Shaojie Tang, Chengfei Lyu, Guihai Chen |
| 2024 | Divide and Denoise: Empowering Simple Models for Robust Semi-Supervised Node Classification against Label Noise. | Kaize Ding, Xiaoxiao Ma, Yixin Liu, Shirui Pan |
| 2024 | Overview of ACM SIGKDD 2024 AI4Science4AI Special Day. | Wei Ding, Gustau Camps-Valls |
| 2024 | Fast Unsupervised Deep Outlier Model Selection with Hypernetworks. | Xueying Ding, Yue Zhao, Leman Akoglu |
| 2024 | Recent and Upcoming Developments in Randomized Numerical Linear Algebra for Machine Learning. | Michal Derezinski, Michael W. Mahoney |
| 2024 | MMBee: Live Streaming Gift-Sending Recommendations via Multi-Modal Fusion and Behaviour Expansion. | Jiaxin Deng, Shiyao Wang, Yuchen Wang, Jiansong Qi, Liqin Zhao, Guorui Zhou, Gaofeng Meng |
| 2024 | Time-Aware Attention-Based Transformer (TAAT) for Cloud Computing System Failure Prediction. | Lingfei Deng, Yunong Wang, Haoran Wang, Xuhua Ma, Xiaoming Du, Xudong Zheng, Dongrui Wu |
| 2024 | Advances in Human Event Modeling: From Graph Neural Networks to Language Models. | Songgaojun Deng, Maarten de Rijke, Yue Ning |
| 2024 | Metric Decomposition in A/B Tests. | Alex Deng, Luke Hagar, Nathaniel T. Stevens, Tatiana Xifara, Amit Gandhi |
| 2024 | Unraveling Block Maxima Forecasting Models with Counterfactual Explanation. | Yue Deng, Asadullah Hill Galib, Pang-Ning Tan, Lifeng Luo |
| 2024 | A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys). | Yashar Deldjoo, Zhankui He, Julian J. McAuley, Anton Korikov, Scott Sanner, Arnau Ramisa, Ren Vidal, Maheswaran Sathiamoorthy, Atoosa Kasirzadeh, Silvia Milano |
| 2024 | AGS-GNN: Attribute-guided Sampling for Graph Neural Networks. | Siddhartha Shankar Das, S. M. Ferdous, Mahantesh M. Halappanavar, Edoardo Serra, Alex Pothen |
| 2024 | Neural Retrievers are Biased Towards LLM-Generated Content. | Sunhao Dai, Yuqi Zhou, Liang Pang, Weihao Liu, Xiaolin Hu, Yong Liu, Xiao Zhang, Gang Wang, Jun Xu |
| 2024 | Bias and Unfairness in Information Retrieval Systems: New Challenges in the LLM Era. | Sunhao Dai, Chen Xu, Shicheng Xu, Liang Pang, Zhenhua Dong, Jun Xu |
| 2024 | Leveraging Pedagogical Theories to Understand Student Learning Process with Graph-based Reasonable Knowledge Tracing. | Jiajun Cui, Hong Qian, Bo Jiang, Wei Zhang |