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