| 2024 | Scalable Transformer for High Dimensional Multivariate Time Series Forecasting. | Xin Zhou, Weiqing Wang, Wray L. Buntine, Shilin Qu, Abishek Sriramulu, Weicong Tan, Christoph Bergmeir |
| 2024 | Multi-Scale Contrastive Attention Representation Learning for Encrypted Traffic Classification. | Shuo Yang, Xinran Zheng, Jinze Li, Jinfeng Xu, Edith C. H. Ngai |
| 2024 | Hierarchical Spatio-Temporal Graph Learning Based on Metapath Aggregation for Emergency Supply Forecasting. | Li Lin, Kaiwen Xia, Anqi Zheng, Shijie Hu, Shuai Wang |
| 2024 | DIFN: A Dual Intention-aware Network for Repurchase Recommendation with Hierarchical Spatio-temporal Fusion. | Li Lin, Xin Xu, Hai Wang, Tian He, Desheng Zhang, Shuai Wang |
| 2024 | Efficient and Secure Contribution Estimation in Vertical Federated Learning. | Juan Li, Rui Deng, Tianzi Zang, Mingqi Kong, Kun Zhu |
| 2024 | Hierarchical Information Propagation and Aggregation in Disentangled Graph Networks for Audience Expansion. | Li Lin, Xinyao Chen, Kaiwen Xia, Shuai Wang, Desheng Zhang, Tian He |
| 2024 | InfinityMath: A Scalable Instruction Tuning Dataset in Programmatic Mathematical Reasoning. | Bo-Wen Zhang, Yan Yan, Lin Li, Guang Liu |
| 2024 | MPHDetect: Multi-View Prompting and Hypergraph Fusion for Malevolence Detection in Dialogues. | Bo Xu, Xuening Qiao, Hongfei Lin, Linlin Zong |
| 2024 | Demonstration of a Multi-agent Framework for Text to SQL Applications with Large Language Models. | Chen Shen, Jin Wang, Sajjadur Rahman, Eser Kandogan |
| 2024 | AlignRec: Aligning and Training in Multimodal Recommendations. | Yifan Liu, Kangning Zhang, Xiangyuan Ren, Yanhua Huang, Jiarui Jin, Yingjie Qin, Ruilong Su, Ruiwen Xu, Yong Yu, Weinan Zhang |
| 2024 | CourIRL: Predicting Couriers' Behavior in Last-Mile Delivery Using Crossed-Attention Inverse Reinforcement Learning. | Shuai Wang, Tongtong Kong, Baoshen Guo, Li Lin, Haotian Wang |
| 2024 | H2D: Hierarchical Heterogeneous Graph Learning Framework for Drug-Drug Interaction Prediction. | Ran Zhang, Xuezhi Wang, Sheng Wang, Kunpeng Liu, Yuanchun Zhou, Pengfei Wang |
| 2024 | Learnable Item Tokenization for Generative Recommendation. | Wenjie Wang, Honghui Bao, Xinyu Lin, Jizhi Zhang, Yongqi Li, Fuli Feng, See-Kiong Ng, Tat-Seng Chua |
| 2024 | Boosting Entity Recognition by leveraging Cross-task Domain Models for Weak Supervision. | Sanjay Agrawal, Srujana Merugu, Vivek Sembium |
| 2024 | Multi-Granularity Modeling in Recommendation: from the Multi-Scenario Perspective. | Yuhao Wang |
| 2024 | Multi-turn Classroom Dialogue Dataset: Assessing Student Performance from One-on-one Conversations. | Jiahao Chen, Zitao Liu, Mingliang Hou, Xiangyu Zhao, Weiqi Luo |
| 2024 | LLM4MSR: An LLM-Enhanced Paradigm for Multi-Scenario Recommendation. | Yuhao Wang, Yichao Wang, Zichuan Fu, Xiangyang Li, Wanyu Wang, Yuyang Ye, Xiangyu Zhao, Huifeng Guo, Ruiming Tang |
| 2024 | Factor Model-Based Large Covariance Estimation from Streaming Data Using a Knowledge-Based Sketch Matrix. | Xiao Tan, Zhaoyang Wang, Hao Qian, Jun Zhou, Peibo Duan, Dian Shen, Meng Wang, Beilun Wang |
| 2024 | Hypergraph Hash Learning for Efficient Trajectory Similarity Computation. | Yuan Cao, Lei Li, Xiangru Chen, Xue Xu, Zuojin Huang, Yanwei Yu |
| 2024 | Improving Adversarial Transferability via Frequency-Guided Sample Relevance Attack. | Xinyi Wang, Zhibo Jin, Zhiyu Zhu, Jiayu Zhang, Huaming Chen |
| 2024 | Towards Efficient Temporal Graph Learning: Algorithms, Frameworks, and Tools. | Ruijie Wang, Wanyu Zhao, Dachun Sun, Charith Mendis, Tarek F. Abdelzaher |
| 2024 | MTSCI: A Conditional Diffusion Model for Multivariate Time Series Consistent Imputation. | Jianping Zhou, Junhao Li, Guanjie Zheng, Xinbing Wang, Chenghu Zhou |
| 2024 | Multivariate Time-Series Anomaly Detection based on Enhancing Graph Attention Networks with Topological Analysis. | Zhe Liu, Xiang Huang, Jingyun Zhang, Zhifeng Hao, Li Sun, Hao Peng |
| 2024 | General Time Transformer: an Encoder-only Foundation Model for Zero-Shot Multivariate Time Series Forecasting. | Cheng Feng, Long Huang, Denis Krompass |
| 2024 | PARs: Predicate-based Association Rules for Efficient and Accurate Anomaly Explanation. | Cheng Feng |