Plenary Session 1: Graph Neural Networks and Inferences (11.03, 10:30 – 12:15)
Graph Disentangle Causal Model: Enhancing Causal Inference in Networked Observational Data: Binbin Hu, Zhicheng An, Zhengwei Wu, Ke Tu, Ziqi Liu, Zhiqiang Zhang, Jun Zhou, Yufei Feng, Jiawei Chen
CIMAGE: Exploiting the Conditional Independence in Masked Graph Auto-encoders: Jongwon Park, Heesoo Jung, Hogun Park
A Sublinear Algorithm for Approximate Shortest Paths in Large Networks: Sabyasachi Basu, Nadia Köshima, Talya Eden, Omri Ben Eliezer, C. Seshadhri
Polaris: Sampling from the Multigraph Configuration Model with Prescribed Color Assortativity: Giulia Preti, Matteo Riondato, Aristides Gionis, Gianmarco De Francisci Morales
DiffGraph: Heterogeneous Graph Diffusion Model: Zongwei Li, Lianghao Xia, Hua Hua, Shijie Zhang, Shuangyang Wang, Chao Huang
Poster Session 1 (11.03, 10:30 – 12:15)
Mitigating Overfitting in Graph Neural Networks via Feature and Hyperplane Perturbation: Yoonhyuk Choi, Jiho Choi, Taewook Ko, Chong-kwon Kim
Dynamic Graph Transformer with Correlated Spatial-Temporal Positional Encoding: Zhe Wang, Sheng Zhou, Jiawei Chen, Zhen Zhang, Binbin Hu, Yan Feng, Chun Chen, Can Wang
S-Diff: An Anisotropic Diffusion Model for Collaborative Filtering in Spectral Domain: Rui Xia, Yanhua Cheng, Yongxiang Tang, Xiaocheng Liu, Xialong Liu, Lisong Wang, Peng Jiang
Maintaining k-MinHash Signatures over Fully-Dynamic Data Streams with Recovery: Andrea Clementi, Luciano Gualà, Luca Pepè Sciarria, Alessandro Straziota
Hyperdimensional Representation Learning for Node Classification and Link Prediction: Abhishek Dalvi, Vasant Honavar
Prospective Multi-Graph Cohesion for Multivariate Time Series Anomaly Detection: Jiazhen Chen, Mingbin Feng, Tony S. Wirjanto
Large Language Model driven Policy Exploration for Recommender Systems: Jie Wang, Alexandros Karatzoglou, Ioannis Arapakis, Joemon M. Jose
Plenary Session 2: Recommendation Systems (11.03, 13:45 – 15:30)
A Contrastive Framework with User, Item and Review Alignment for Recommendation: Hoang V. Dong, Yuan Fang, Hady W. Lauw
Facet-Aware Multi-Head Mixture-of-Experts Model for Sequential Recommendation: Mingrui Liu, Sixiao Zhang, Cheng Long
MixRec: Heterogeneous Graph Collaborative Filtering: Lianghao Xia, Meiyan Xie, Yong Xu, Chao Huang
Review-Based Hyperbolic Cross-Domain Recommendation: Yoonhyuk Choi, Jiho Choi, Taewook Ko, Chong-Kwon Kim
VARIUM: Variational Autoencoder for Multi-Interest Representation with Inter-User Memory: Nhu-Thuat Tran, Hady W. Lauw
Poster Session 2 (11.03, 13:45 – 15:30)
The Initial Screening Order Problem: Jose M. Alvarez, Antonio Mastropietro, Salvatore Ruggieri
Cross-Domain Pre-training with Language Models for Transferable Time Series Representations: Mingyue Cheng, Xiaoyu Tao, Qi Liu, Hao Zhang, Yiheng Chen, Defu Lian
Unsupervised Robust Cross-Lingual Entity Alignment via Neighbor Triple Matching with Entity and Relation Texts: Soojin Yoon, Sungho Ko, TongYoung Kim, SeongKu Kang, Jinyoung Yeo, Dongha Lee
Q-DISCO: Query-Centric Densest Subgraphs in Networks with Opinion Information: Tianyi Chen, Atsushi Miyauchi, Charalampos E. Tsourakakis
Gradient Deconfliction via Orthogonal Projections onto Subspaces For Multi-task Learning: Shijie Zhu, Hui Zhao, Tianshu Wu, Pengjie Wang, Hongbo Deng, Jian Xu, Bo Zheng
Self-supervised Time-aware Heterogeneous Hypergraph Learning for Dynamic Graph-level Classification: Malik Khizar Hayat, Shan Xue, Jia Wu, Bilal Khan, Jian Yang
Combating Heterogeneous Model Biases in Recommendations via Boosting: Jinhao Pan, James Caverlee, Ziwei Zhu
Plenary Session 3: Large Language Models (11.03, 16:00 – 17:45)
LOGIN: A Large Language Model Consulted Graph Neural Network Training Framework: Yiran Qiao, Xiang Ao, Yang Liu, Jiarong Xu, Xiaoqian Sun, Qing He
MoKGNN: Boosting Graph Neural Networks via Mixture of Generic and Task-Specific Language Models: Hao Yan, Chaozhuo Li, Jun Yin, Weihao Han, Hao Sun, Senzhang Wang, Jian Zhang, Jianxin Wang
Beyond Answers: Transferring Reasoning Capabilities to Smaller LLMs Using Multi-Teacher Knowledge Distillation: Yijun Tian, Yikun Han, Xiusi Chen, Wei Wang, Nitesh V. Chawla
Large Language Model Simulator for Cold-Start Recommendation: Feiran Huang, Yuanchen Bei, Zhenghang Yang, Junyi Jiang, Hao Chen, Qijie Shen, Senzhang Wang, Fakhri Karray, Philip S Yu
Lighter And Better: Towards Flexible Context Adaptation For Retrieval Augmented Generation: Chenyuan Wu, Ninglu Shao, Zheng Liu, Shitao Xiao, Chaozhuo Li, Chen Zhang, Senzhang Wang, Defu Lian
Poster Session 3 (11.03, 16:00 – 17:45)
Robustness Verification of Deep Graph Neural Networks Tightened by Linear Approximation: Xingyu Zeng, Han Li, Qi Qi, Jingyu Wang, Haodong Deng, Haifeng Sun, Zirui Zhuang, Jianxin Liao
Dynamic Interaction-Driven Intent Evolver with Semantic Probability Distributions: Zelin Li, Cheng Zhang, Dawei Song
DDualSE: Decoupled Dual-head Squeeze and Excitation Attention for Sequential Recommendation: Nijia Mo, Jianxiang Zang, Zhan Wang, Hui Liu
Do Stubborn Users Always Cause More Polarization and Disagreement? A Mathematical Study: Mohammad Shirzadi, Ahad N. Zehmakan
HHGT: Hierarchical Heterogeneous Graph Transformer for Heterogeneous Graph Representation Learning: Qiuyu Zhu, Liang Zhang, Qianxiong Xu, Kaijun Liu, Cheng Long, Xiaoyang Wang
Privacy-Preserving Orthogonal Aggregation for Guaranteeing Gender Fairness in Federated Recommendation: Siqing Zhang, Yuchen Ding, Wei Tang, Wei Sun, Yong Liao, Peng Yuan Zhou
Writing Style Matters: An Examination of Bias and Fairness in Information Retrieval Systems: Hongliu Cao
Plenary Session 4: Sequential and Temporal Data Modeling (12.03, 10:30 – 12:15)
Sequential diversification with provable guarantees: Honglian Wang, Sijing Tu, Aristides Gionis
Temporal Linear Item-Item Model for Sequential Recommendation: Seongmin Park, Mincheol Yoon, Minjin Choi, Jongwuk Lee
Oracle-guided Dynamic User Preference Modeling for Sequential Recommendation: Jiafeng Xia, Dongsheng Li, Hansu Gu, Tun Lu, Peng Zhang, Li Shang, Ning Gu
Neo-TKGC: Enhancing Temporal Knowledge Graph Completion with Integrated Node Weights and Future Information: Zihan Qiu, Xiaoling Zhou, Chunyan An, Qiang Yang, Zhixu Li
Poster Session 4 (12.03, 10:30 – 12:15)
BAKER: Bayesian Kernel Uncertainty in Domain-Specific Document Modelling: Ubaid Azam, Imran Razzak, Shelly Vishwakarma, Hakim Hacid, Dell Zhang, Shoaib Jameel
Edge Classification on Graphs: New Directions in Topological Imbalance: Xueqi Cheng, Yu Wang, Yunchao Liu, Yuying Zhao, Charu C. Aggarwal, Tyler Derr
Hawkes Point Process-enhanced Dynamic Graph Neural Network: Zhiqiang Wang, Baijing hu, Kaixuan Yao, Jiye Liang
Optimizing Blockchain Analysis: Tackling Temporality and Scalability with an Incremental Approach with Metropolis-Hastings Random Walks: Junliang Luo, Xue Liu
SCONE: A Novel Stochastic Sampling to Generate Contrastive Views and Hard Negative Samples for Recommendation: Chaejeong Lee, Jeongwhan Choi, Hyowon Wi, Sung-Bae Cho, Noseong Park
Towards Personalized Federated Multi-Scenario Multi-Task Recommendation: Yue Ding, Yanbiao Ji, Xun Cai, Xin Xin, Yuxiang Lu, Suizhi Huang, Chang Liu, Xiaofeng Gao, Tsuyoshi Murata, Hongtao Lu
ESA: Example Sieve Approach for Multi-Positive and Unlabeled Learning: Zhongnian Li, Meng Wei, Peng Ying, Xinzheng Xu
Plenary Session 5: Graph Learning and Adaptation (12.03, 13:45 – 15:30)
FedGF: Enhancing Structural Knowledge via Graph Factorization for Federated Graph Learning: Pengyang Zhou, Chaochao Chen, Weiming Liu, Xinting Liao, Fengyuan Yu, Zhihui Fu, Xingyu Lou, Wu Wen, Xiaolin Zheng, Jun Wang
Graph Size-imbalanced Learning with Energy-guided Structural Smoothing: Jiawen Qin, Pengfeng Huang, Qingyun Sun, Cheng Ji, Xingcheng Fu, Jianxin Li
Inductive Graph Few-shot Class Incremental Learning: Yayong Li, Peyman Moghadam, Can Peng, Nan Ye, Piotr Koniusz
RSM: Reinforced Subgraph Matching Framework with Fine-grained Operation based Search Plan: Ziming Li, Yuequn Dou, Youhuan Li, Xinhuan Chen, Chuxu Zhang
Incomplete Multi-view Clustering via Local Reasoning and Correlation Analysis: Xiaocui Li, Guoliang Li, Xinyu Zhang, Yangtao Wang, Qingyu Shi, Wei Liang
Poster Session 5 (12.03, 13:45 – 15:30)
Context Embeddings for Efficient Answer Generation in Retrieval-Augmented Generation: David Rau, Shuai Wang, Hervé Déjean, Stéphane Clinchant, Jaap Kamps
An aspect performance-aware hypergraph neural network for review-based recommendation: Junrui Liu, Tong Li, Di Wu, Zifang Tang, Yuan Fang, Zhen Yang
Balancing Revenue and Privacy with Signaling Schemes in Online Ad Auctions: Hongtao Liu, Luxi Chen, Yiming Ding, Changcheng Li, Han Li, Peng Jiang, Weiran Shen
DeMBR: Denoising Model with Memory Pruning and Semantic Guidance for Multi-Behavior Recommendation: Shuai Zhang, Hua Chu, Jianan Li, Yangtao Zhou, Shirong Wang, Qiaofei Sun
Progressive Tasks Guided Multi-Source Network for Customer Lifetime Value Prediction in Online Advertising: Zheng Pan, Xingyu Lou, Xiao Jin, Chiye Ou, Feng Liu, Tieyong Zeng, Chengwei He, Xiang Liu, Lilong Wei, Jun Wang
Mining Topics towards ChatGPT Using a Disentangled Contextualized-neural Topic Model: Rui Wang, Xing Liu, Yanan Wang, Shuyu Chang, Yuanzhi Yao, Haiping Huang
LightGNN: Simple Graph Neural Network for Recommendation: Guoxuan Chen, Lianghao Xia, Chao Huang
Plenary Session 6: Fake News and Anomaly Detection (12.03, 16:00 – 17:45)
Revisiting Fake News Detection: Towards Temporality-aware Evaluation by Leveraging Engagement Earliness: Junghoon Kim, Junmo Lee, Yeonjun In, Kanghoon Yoon, Chanyoung Park
D 2: Customizing Two-Stage Graph Neural Networks for Early Rumor Detection through Cascade Diffusion Prediction: Haowei Xu, Xianghua Li, Chao Gao, Zhen Wang
Adjacent Neighborhood Transformer-based Diffusion Model for Anomaly Detection under Incomplete Industrial Data Sources: Chengqing Li, Lulu Wang
GAMED: Knowledge Adaptive Multi-Experts Decoupling for Multimodal Fake News Detection: Lingzhi Shen, Yunfei Long, Xiaohao Cai, Imran Razzak, Guanming Chen, Kang Liu, Shoaib Jameel
Poster Session 6 (12.03, 16:00 – 17:45)
Enhancing Code Search Intent with Programming Context Exploration: Yanmin Dong, Zhenya Huang, zheng zhang, GuanHao Zhao, Likang Wu, Hongke Zhao, Binbin Jin, Qi Liu
AMLCDR: An Adaptive Meta-Learning Model for Cross-Domain Recommendation by Aligning Preference Distributions: Fanqi Meng, Zhiyuan Zhang
HACD: Harnessing Attribute Semantics and Mesoscopic Structure for Community Detection: Anran Zhang, Xingfen Wang, Yuhan Zhao
IMPO: Interpretable Memory-based Prototypical Pooling: Alessio Ragno, Roberto Capobianco
Personalised Outfit Recommendation via History-aware Transformers: Myong Chol Jung, Julien Monteil, Philip Schulz, Volodymyr Vaskovych
DTPN: A Diffusion-based Traffic Purification Network for Tor Website Fingerprinting: Chenchen Yang, Xi Xiao, guangwu hu, Zhen Ling, Hao Li, Bin Zhang
Density-aware and Cluster-based Federated Anomaly Detection on Data Streams: Bin Li, Li Cheng, Zheng Qin, Yunlong Wu
Plenary Session 7: Bias in Recommendations (13.03, 10:30 – 12:15)
How Do Recommendation Models Amplify Popularity Bias? An Analysis from the Spectral Perspective: Siyi Lin, Chongming Gao, Jiawei Chen, Sheng Zhou, Binbin Hu, Yan Feng, Chun Chen, Can Wang
Exploration and Exploitation of Hard Negative Samples for Cross-Domain Sequential Recommendation: Yidan Wang, Xuri Ge, Xin Chen, Ruobing Xie, Su Yan, Xu Zhang, Zhumin Chen, Jun Ma, Xin Xin
Bridging Source and Target Domains via Link Prediction for Unsupervised Domain Adaptation on Graphs: Yilong Wang, Tianxiang Zhao, Zongyu Wu, Suhang Wang
Your causal self-attentive recommender hosts a lonely neighborhood: Yueqi Wang, Zhankui He, Zhenrui Yue, Julian McAuley, Dong Wang
Poster Session 7 (13.03, 10:30 – 12:15)
Training MLPs on Graphs without Supervision: Zehong Wang, Zheyuan Zhang, Chuxu Zhang, Yanfang Ye
Explainable CTR prediction via LLM reasoning: Xiaohan Yu, Li Zhang, Chong Chen
Adaptive Graph Enhancement for Imbalanced Multi-relation Graph Learning: Yiyue Qian, Tianyi Ma, Chuxu Zhang, Yanfang Ye
DimeRec: A Unified Framework for Enhanced Sequential Recommendation via Generative Diffusion Models: Wuchao Li, Rui Huang, Haijun Zhao, Chi Liu, Kai Zheng, Qi Liu, Na Mou, Guorui Zhou, Defu Lian, Yang Song, Wentian Bao, Enyun Yu, Wenwu Ou
An Edge-Based Decomposition Framework for Temporal Networks: Lutz Oettershagen, Athanasios L. Konstantinidis, Giuseppe F. Italiano
Fusion Matters: Learning Fusion in Deep Click-through Rate Prediction Models: Kexin Zhang, Fuyuan Lyu, Xing Tang, Dugang Liu, Chen Ma, Kaize Ding, Xiuqiang He, Xue Liu
Towards Reliable Latent Knowledge Estimation in LLMs: Zero-Prompt Many-Shot Based Factual Knowledge Extraction: Qinyuan Wu, Mohammad Aflah Khan, Soumi Das, Vedant Nanda, Bishwamittra Ghosh, Camila Kolling, Till Speicher, Laurent Bindschaedler, Krishna Gummadi, Evimaria Terzi
Plenary Session 8: Multimodal Data and Time Series Analysis (13.03, 13:45 – 15:30)
MedTransTab: Advancing Medical Cross-Table Tabular Data Generation: Yuyan Chen, Qingpei Guo, Shuangjie You, Zhixu Li
Spectrum-based Modality Representation Fusion Graph Convolutional Network for Multimodal Recommendation: Rongqing Kenneth Ong, Andy W. H. Khong
Teach Me How to Denoise: A Universal Framework for Denoising Multi-modal Recommender Systems via Guided Calibration: Hongji Li, Hanwen Du, Youhua li, Junchen Fu, Chunxiao Li, Ziyi Zhuang, Jiakang Li, Yongxin Ni
InstrucTime: Advancing Time Series Classification with Multimodal Language Modeling: Mingyue Cheng, Yiheng Chen, Qi Liu, Zhiding Liu, Yucong Luo, Enhong Chen
Poster Session 8 (13.03, 13:45 – 15:30)
Improving FIM Code Completions via Context & Curriculum Based Learning: Hitesh Sagtani, Rishabh Mehrotra, Beyang Liu
Sequentially Diversified and Accurate Recommendations in Chronological Order for a Series of Users: Jongjin Kim, U Kang
Untapping the Power of Indirect Relationships in Entity Summarization: Atefeh Moradan, Mohammad Sorkhpar, Atsushi Miyauchi, Davide Mottin, Ira Assent
Heterophilic Graph Neural Networks Optimization with Causal Message-passing: Botao Wang, Jia Li, Heng Chang, Keli Zhang, Fugee Tsung
HaGAR: Hardness-aware Generative Adversarial Recommender: Yuan-Heng Lee, Josh Jia-Ching Ying, Vincent S. Tseng
UIPN: User Intent Profiling Network for Multi Behavior Modeling in CTR Prediction: Xu Yang, Guangyuan Yu, Jun He
DLCRec: A Novel Approach for Managing Diversity in LLM-Based Recommender Systems: Jiaju Chen, Chongming Gao, Shuai Yuan, Shuchang Liu, Qingpeng Cai, Peng Jiang
Reindex-Then-Adapt: Improving Large Language Models for Conversational Recommendation: Zhankui He, Zhouhang Xie, Harald Steck, Dawen Liang, Rahul Jha, Nathan Kallus, Julian McAuley
Plenary Session 9: Emerging Topics in Data Mining (13.03, 16:00 – 17:45)
Improving CTR Prediction with Graph-Enhanced Interest Networks for Sparse Behavior Sequences: Xuanzhou Liu, Zhibo Xiao, Luwei Yang, Hansheng Xue, Jianxing Ma, Yujiu Yang
Predicting Eviction Status Using Airbnb Data in the Absence of Ground-Truth Eviction Records: Maryam Tabar, Anusha Abdulla, J. Andrew Petersen, Dongwon Lee
Improving Scientific Document Retrieval with Concept Coverage-based Query Set Generation: SeongKu Kang, Bowen Jin, Wonbin Kweon, Yu Zhang, Dongha Lee, Jiawei Han, Hwanjo Yu
Demystify Epidemic Containment in Directed Networks: Theory and Algorithms: Yinhan He, Chen Chen, Song Wang, Guanghui Min, Jundong Li
Poster Session 9 (13.03, 16:00 – 17:45)
Adaptive Loss-based Curricula for Neural Team Recommendation: Reza Barzegar, Marco Kurepa, Hossein Fani
How Does Memorization Impact LLMs’ Social Reasoning? An Assessment using Seen and Unseen Queries: Maryam Amirizaniani, Maryna Sivachenko, Adrian Lavergne, Chirag Shah, Afra Mashhadi
RetriEVAL: Evaluating Text Generation with Contextualized Lexical Match: Zhen Li, Xinchi Li, Chongyang Tao, Jiazhan Feng, Tao Shen, Can Xu, Hao Wang, Dongyan Zhao, Shuai Ma
MCRanker: Generating Diverse Criteria On-the-Fly to Improve Pointwise LLM Rankers: Fang Guo, Wenyu Li, Honglei Zhuang, Yun Luo, Yafu Li, Le Yan, Qi Zhu, Yue Zhang
Quam: Adaptive Retrieval through Query Affinity Modelling: Mandeep Rathee, Sean MacAvaney, Avishek Anand
ProCC: Programmatic Reinforcement Learning for Efficient and Transparent TCP Congestion Control: Yin Gu, Kai Zhang, Qi Liu, Runlong Yu, Xin Lin, Xinjie Sun
UniGLM: Training One Unified Language Model for Text-Attributed Graphs Embedding: Yi Fang, Dongzhe Fan, Sirui Ding, Ninghao Liu, Qiaoyu Tan
HTEA: Heterogeneity-aware Embedding Learning for Temporal Entity Alignment: Jiayun Li, Wen Hua, Fengmei Jin, Xue Li