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ORCIDKDD 2025: Toronto ON, Canada
- Luiza Antonie, Jian Pei, Xiaohui Yu, Flavio Chierichetti, Hady W. Lauw, Yizhou Sun, Srinivasan Parthasarathy:
Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.2, KDD 2025, Toronto ON, Canada, August 3-7, 2025. ACM 2025, ISBN 979-8-4007-1454-2
Keynote Talks
- Christopher D. Manning:
The Surprising Victory of NLP: From Philosophy to Agentic Language Models. 1 - Dan Roth:
On Reasoning LLMs: Myths, Merits, and How to Move Forward. 2 - Caroline Uhler:
Causality - Exploiting Multi-Modal Data. 3-4
Research Track
- Tassallah Abdullahi, Ioanna Gemou, Nihal V. Nayak, Ghulam Murtaza, Stephen H. Bach, Carsten Eickhoff, Ritambhara Singh:
K-Paths: Reasoning over Graph Paths for Drug Repurposing and Drug Interaction Prediction. 5-16 - Florian Adriaens, Nikolaj Tatti:
Fair Diversity Maximization with Few Representatives. 17-25 - Daniel Alabi, Dimitris Kalimeris:
Separating Graph Generative Models via Degree Distributions. 26-36 - Niloufar Alipour Talemi, Hossein Kashiani, Hossein R. Nowdeh, Fatemeh Afghah:
DiSa: Directional Saliency-Aware Prompt Learning for Generalizable Vision-Language Models. 37-46 - Sofiane Azogagh, Zelma Aubin Birba, Josée Desharnais, Sébastien Gambs, Marc-Olivier Killijian, Nadia Tawbi:
GRAND : Graph Reconstruction from Potential Partial Adjacency and Neighborhood Data. 47-58 - Jeongmin Bae, Donghyoung Han, Min-Soo Kim:
FlexGNN: A High-Performance, Large-Scale Full-Graph GNN System with Best-Effort Training Plan Optimization. 59-70 - Jun Bai, Yiliao Song, Di Wu, Atul Sajjanhar, Yong Xiang, Wei Zhou, Xiaohui Tao, Yan Li, Yue Li:
A Unified Solution to Diverse Heterogeneities in One-Shot Federated Learning. 71-82 - Yibing Bai, Min Gao, Zongwei Wang, Xinyi Gao, Wentao Li:
Progressive Stacking for Scalable Graph Condensation. 83-94 - Lujie Ban, Xiaolin Han, Jinyang Li, Chenhao Ma:
UnG-MoCha: Neural Motif Counting in Uncertain Graphs. 95-106 - Jianyuan Bo, Hao Wu, Yuan Fang:
Quantizing Text-attributed Graphs for Semantic-Structural Integration. 107-118 - Xuemei Cao, Hanlin Gu, Xin Yang, Bingjun Wei, Haoyang Liang, Xiangkun Wang, Tianrui Li:
ErrorEraser: Unlearning Data Bias for Improved Continual Learning. 119-130 - Chia-Yuan Chang, Yu-Neng Chuang, Zhimeng Jiang, Kwei-Herng Lai, Anxiao Jiang, Na Zou:
CODA: Temporal Domain Generalization via Concept Drift Simulator. 131-142 - Chao Chen, Tian Zhou, Yanjun Zhao, Hui Liu, Rong Jin, Liang Sun:
Does Vector Quantization Fail in Spatio-Temporal Forecasting? Exploring a Differentiable Sparse Soft-Vector Quantization Approach. 143-154 - Jialei Chen, Yuanbo Xu, Yiheng Jiang:
Unlocking the Power of Diffusion Models in Sequential Recommendation: A Simple and Effective Approach. 155-166 - Jiawen Chen, Qi Shao, Duxin Chen, Wenwu Yu:
Decoupling Spatio-Temporal Prediction: When Lightweight Large Models Meet Adaptive Hypergraphs. 167-178 - Jingyan Chen, Guanghui Zhu, Guansong Pang, Chunfeng Yuan, Yihua Huang:
AffinityTune: A Prompt-Tuning Framework for Few-Shot Anomaly Detection on Graphs. 179-190 - Junze Chen, Cheng Yang, Shujie Li, Zhiqiang Zhang, Yawen Li, Junping Du, Chuan Shi:
GraphLAMA: Enabling Efficient Adaptation of Graph Language Models with Limited Annotations. 191-202 - Mengjie Chen, Ming Zhang, Cunquan Qu:
Towards Interpretable Drug-Drug Interaction Prediction: A Graph-Based Approach with Molecular and Network-Level Explanations. 203-214 - Min Chen, Weizhuo Gao, Chen Wang, Gaoyang Liu, Ahmed M. Abdelmoniem, Kai Peng:
From Expansion to Retraction: Long-tailed Machine Unlearning via Boundary Manipulation. 215-226 - Rongqin Chen, Yan Li, Dan Wu, Fan Mo, Shenghui Zhang, Pak Lon Ip, Hoi Cheong Iam, Ye Li, Leong Hou U:
Enhanced Subgraph Learning in 2-FWL GNNs via Local Connectivity, Spectral, and Distance Encodings. 227-238 - Shuyi Chen, Shixiang Zhu:
Counterfactual Fairness Through Transforming Data Orthogonal to Bias. 239-249 - Weijun Chen, Shun Li, Heyuan Wang, Tengjiao Wang:
Enhancer: A Distribution-Aware Framework with Temporal-Relational Meta-Learning for Stock Prediction. 250-261 - Yile Chen, Yicheng Tao, Yue Jiang, Shuai Liu, Han Yu, Gao Cong:
Enhancing Large Language Models for Mobility Analytics with Semantic Location Tokenization. 262-273 - Zhaoliang Chen, Zhihao Wu, William K. Cheung, Hong-Ning Dai, Byron Choi, Jiming Liu:
MSHTrans: Multi-Scale Hypergraph Transformer with Time-Series Decomposition for Temporal Anomaly Detection. 274-285 - Zheng Chen, Feng Zhang, Yifei Xia, Wentao Zhang, Xiaowei Zhu, Wenguang Chen, Xiaoyong Du:
CompressGNN: Accelerating Graph Neural Network Training via Hierarchical Compression. 286-297 - Ke Cheng, Linzhi Peng, Pengyang Wang, Heng Chang, Junchen Ye, Bowen Du:
On the Scalability of Temporal Relative Positional Encoding for Dynamic Link Prediction. 298-309 - Rui Cheng, Xiangfei Jia, Qing Li, Rong Xing, Jiwen Huang, Yu Zheng, Zhilong Xie:
FAT: Frequency-Aware Pretraining for Enhanced Time-Series Representation Learning. 310-321 - Zhan Cheng, Bolin Shen, Tianming Sha, Yuan Gao, Shibo Li, Yushun Dong:
ATOM: A Framework of Detecting Query-Based Model Extraction Attacks for Graph Neural Networks. 322-333 - Zhangtao Cheng, Yuhao Ma, Jian Lang, Kunpeng Zhang, Ting Zhong, Yong Wang, Fan Zhou:
Generative Thinking, Corrective Action: User-Friendly Composed Image Retrieval via Automatic Multi-Agent Collaboration. 334-344 - Alberto Silvio Chiappa, Briti Gangopadhyay, Zhao Wang, Shingo Takamatsu:
Auto-Bidding in Real-Time Auctions via Oracle Imitation Learning. 345-356 - Dominic Coey, Kenneth Hung:
Empirical Bayes Selection for Value Maximization. 357-368 - Erica Coppolillo, Federico Cinus, Marco Minici, Francesco Bonchi, Giuseppe Manco:
Engagement-Driven Content Generation with Large Language Models. 369-379 - Mustafa Coskun, Abdelkader Baggag, Mehmet Koyutürk:
ArnoldiGCL: Graph Contrastive Learning via Learnable Arnoldi-Based Guided Spectral Chebyshev Polynomial Filters. 380-391 - Xiaoxi Cui, Yurong Cheng, Xiangmin Zhou, Yongjiao Sun:
Cross-Platform Online Team Formation in Spatial Crowdsourcing. 392-403 - Longchao Da, Rui Wang, Xiaojian Xu, Parminder Bhatia, Taha A. Kass-Hout, Hua Wei, Cao Xiao:
FlanS: A Foundation Model for Free-Form Language-based Segmentation in Medical Images. 404-414 - Enyan Dai, Minhua Lin, Suhang Wang:
PreGIP: Watermarking the Pretraining of Graph Neural Networks for Deep IP Protection. 415-426 - Xiangxiang Dai, Xiaowei Sun, Jinhang Zuo, Xutong Liu, John C. S. Lui:
A Unified Online-Offline Framework for Co-Branding Campaign Recommendations. 427-438 - M. Clara De Paolis Kaluza, Thulasi Tholeti, Yile Chen, Ricardo Baeza-Yates, Predrag Radivojac, Shantanu Jain:
Are Your Fairness Metrics Accurate? A Semi-Supervised Approach to Improving Fairness Estimates Under Sample Selection Bias. 439-450 - Mohsen Dehghankar, Abolfazl Asudeh:
Rank It, Then Ask It: Input Reranking for Maximizing the Performance of LLMs on Symmetric Tasks. 451-462 - Bangchao Deng, Ling Ding, Lianhua Ji, Chunhua Chen, Xin Jing, Bingqing Qu, Dingqi Yang:
Marionette: Fine-Grained Conditional Generative Modeling of Spatiotemporal Human Trajectory Data Beyond Imitation. 463-473 - Bowen Deng, Chang Xu, Hao Li, Yu-Hao Huang, Min Hou, Jiang Bian:
TarDiff: Target-Oriented Diffusion Guidance for Synthetic Electronic Health Record Time Series Generation. 474-485 - Chaoyi Deng, Jialong Wu, Ningya Feng, Jianmin Wang, Mingsheng Long:
CompilerDream: Learning a Compiler World Model for General Code Optimization. 486-497 - Sergio Díaz-Aranda, Juan Marcos Ramirez, Mohit Daga, Jaya Prakash Champati, Jose Aguilar, Rosa E. Lillo, Antonio Fernández Anta:
Error Bounds for the Network Scale-Up Method. 498-509 - Kaiqi Ding, Yuanmu Ma, Zijian Song, Kaigui Bian:
Enhancing Microservices Anomaly Detection via Multimodal Data Fusion in the Wavelet Domain and Spatiotemporal Graph-based Diffusion Probabilistic Model. 510-520 - Zahra Donyavi, Feiyu Li, Yunrui Zhang, Diego Furtado Silva, Gustavo Batista:
Match: A Maximum-Likelihood Approach for Classification under Label Shift. 521-530 - Haotong Du, Yaqing Wang, Fei Xiong, Lei Shao, Ming Liu, Hao Gu, Quanming Yao, Zhen Wang:
PERSCEN: Learning Personalized Interaction Pattern and Scenario Preference for Multi-Scenario Matching. 531-542 - Huaming Du, Yujia Zheng, Baoyu Jing, Yu Zhao, Gang Kou, Guisong Liu, Tao Gu, Weimin Li, Carl Yang:
Causal Discovery through Synergizing Large Language Model and Data-Driven Reasoning. 543-554 - Danish Ebadulla, Aditya Gulati, Ambuj K. Singh:
Normalized Space Alignment: A Versatile Metric for Representation Analysis. 555-566 - Derek Everett, Fred Lu, Edward Raff, Fernando Camacho, James Holt:
Quick Draw Bandits: Quickly Optimizing in Nonstationary Environments with Extremely Many Arms. 567-578 - Zeheng Fan, Yuxiang Zeng, Zhuanglin Zheng, Binhan Yang, Yongxin Tong:
FedVS: Towards Federated Vector Similarity Search with Filters. 579-590 - Jie Feng, Tianhui Liu, Yuwei Du, Siqi Guo, Yuming Lin, Yong Li:
CityGPT: Empowering Urban Spatial Cognition of Large Language Models. 591-602 - Tingsheng Feng, Zhihao Shen, Xi Zhao, Xiaoni Lu, Yuyang Zhou:
CryptoMixer: Fine-grained market information-aware MLP Networks for Individual Cryptocurrency Trading Prediction. 603-614 - Zihan Feng, Yajun Yang, Xin Huang, Hong Gao, Liping Jing, Qinghua Hu:
Efficient Sphere-Effect Based Information Diffusion Prediction on Large-scale Social Networks. 615-625 - Florian Frantzen, Michael T. Schaub:
HLSAD: Hodge Laplacian-based Simplicial Anomaly Detection. 626-636 - Haoyan Fu, Zhida Qin, Shixiao Yang, Haoyao Zhang, Bin Lu, Shuang Li, Tianyu Huang, John C. S. Lui:
Time Matters: Enhancing Sequential Recommendations with Time-Guided Graph Neural ODEs. 637-648 - Hongfan Gao, Wangmeng Shen, Xiangfei Qiu, Ronghui Xu, Bin Yang, Jilin Hu:
SSD-TS: Exploring the Potential of Linear State Space Models for Diffusion Models in Time Series Imputation. 649-660 - Xinyi Gao, Yayong Li, Tong Chen, Guanhua Ye, Wentao Zhang, Hongzhi Yin:
Contrastive Graph Condensation: Advancing Data Versatility through Self-Supervised Learning. 661-672 - Chen Gong, Rui Xing, Zhenzhe Zheng, Fan Wu:
A Two-Stage Data Selection Framework for Data-Efficient Model Training on Edge Devices. 673-684 - Peiliang Gong, Yucheng Wang, Min Wu, Zhenghua Chen, Xiaoli Li, Daoqiang Zhang:
Temporal Restoration and Spatial Rewiring for Source-Free Multivariate Time Series Domain Adaptation. 685-696 - Sruthi Gorantla, Sara Ahmadian:
Pairwise Sample Complexity for Fair Active Ranking with Cascaded Norm Objectives. 697-708 - Weijie Guan, Haohui Wang, Jian Kang, Lihui Liu, Dawei Zhou:
EVINET: Towards Open-World Graph Learning via Evidential Reasoning Network. 709-720 - Yi Gui, Zhen Li, Zhongyi Zhang, Guohao Wang, Tianpeng Lv, Gaoyang Jiang, Yi Liu, Dongping Chen, Yao Wan, Hongyu Zhang, Wenbin Jiang, Xuanhua Shi, Hai Jin:
LaTCoder: Converting Webpage Design to Code with Layout-as-Thought. 721-732 - Shuyang Guo, Wenjin Xie, Ping Lu, Ting Deng, Richong Zhang, Jianxin Li, Xiangping Huang, Zhongyi Liu:
Improving Subgraph Matching by Combining Algorithms and Graph Neural Networks. 733-744 - Wei Guo, Yiqi Tong, Yiyang Duan, Fuzhen Zhuang, Xiao Zhang, Zhaojun Hu, Jin Dong:
FEZE: Alignment-Flexible Zero-Shot Vertical Federated Learning. 745-754 - Wenqi Guo, Shikui Tu, Lei Xu:
S3GA: Towards Scalable Self-Supervised Learning for Large Scale Graph Alignment. 755-766 - Zhiyu Guo, Yang Liu, Xiang Ao, Qing He:
GRASP: Differentially Private Graph Reconstruction Defense with Structured Perturbation. 767-777 - Anjali Gupta, Prashant Kumar, Aniket Mishra, Abhishek Singh, Surender Kumar, Muthusamy Chelliah, Abhijnan Chakraborty, Sayan Ranu:
Persona Identification in E-Commerce with Scarce Labels and In-Context Graph Learning. 778-789 - Ashutosh Gupta, Thomas A. Henzinger, Konstantin Kueffner, Kaushik Mallik, David Pape:
Monitoring Robustness and Individual Fairness. 790-801 - Minglian Han, Ling Wang, Ye Yuan, Xin Luo:
SGD-DyG: Self-Reliant Global Dependency Apprehending on Dynamic Graphs. 802-813 - Xiao Han, Chen Zhu, Hengshu Zhu, Xiangyu Zhao:
Swarm Intelligence in Geo-Localization: A Multi-Agent Large Vision-Language Model Collaborative Framework. 814-825 - Xiaolin Han, Yikun Zhang, Chenhao Ma, Lingyun Song, Reynold Cheng, Xuequn Shang:
TempASD: Temporal Anomalous Subgraph Discovery in Large-Scale Dynamic Financial Networks. 826-837 - Qi Hao, Yue Gao, Runchang Liang, Yunhe Zhang, Pengyang Wang:
Generative Imputation with Multi-level Causal Consistency for Variable Subset Forecasting. 838-849 - Pavithra Harsha, Chitra Subramanian, Naoki Abe, Shivaram Subramanian, Amadou Ba, Kevin Arturo Fernández Román, Mauricio Longinos Garrido, Chandrasekhar Narayanaswami:
Practical Contextual Bandits for Large-Scale Structured Discrete Constrained Optimization Problems. 850-859 - Buyun He, Xiaorui Jiang, Qi Wu, Hao Liu, Yingguang Yang, Yong Liao:
Boosting Bot Detection via Heterophily-Aware Representation Learning and Prototype-Guided Cluster Discovery. 860-871 - Chuan He, Yongchao Liu, Qiang Li, Weiqiang Wang, Xing Fu, Xinyi Fu, Chuntao Hong, Xinwei Yao:
Multi-Grained Preference Enhanced Transformer for Multi-Behavior Sequential Recommendation. 872-883 - Jesse He, Akbar Rafiey, Gal Mishne, Yusu Wang:
Explaining GNN Explanations with Edge Gradients. 884-895 - Yingzhi He, Xiaohao Liu, An Zhang, Yunshan Ma, Tat-Seng Chua:
LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation. 896-907 - Yuanpeng He, Lijian Li, Tianxiang Zhan, Chi-Man Pun, Wenpin Jiao, Zhi Jin:
Evidential Prototype Learning for Semi-supervised Medical Image Segmentation. 908-919 - Yunhang He, Cong Xu, Jun Wang, Wei Zhang:
Collaborative Filtering Meets Spectrum Shift: Connecting User-Item Interaction with Graph-Structured Side Information. 920-931 - Zijian He, Reyna Abhyankar, Vikranth Srivatsa, Yiying Zhang:
Cognify: Supercharging Gen-AI Workflows With Hierarchical Autotuning. 932-943 - Asela Hevapathige, Ahad N. Zehmakan, Qing Wang:
Depth-Adaptive Graph Neural Networks via Learnable Bakry-Émery Curvature. 944-955 - Yupeng Hou, Jiacheng Li, Ashley Shin, Jinsung Jeon, Abhishek Santhanam, Wei Shao, Kaveh Hassani, Ning Yao, Julian J. McAuley:
Generating Long Semantic IDs in Parallel for Recommendation. 956-966 - Ruofan Hu, Dongyu Zhang, Huayi Zhang, Elke A. Rundensteiner:
CLID-MU: Cross-Layer Information Divergence Based Meta Update Strategy for Learning with Noisy Labels. 967-978 - Zhiwei Hu, Víctor Gutiérrez-Basulto, Zhiliang Xiang, Ru Li, Jeff Z. Pan:
Multi-level Mixture of Experts for Multimodal Entity Linking. 979-990 - Shaoyuan Huang, Tiancheng Zhang, Zhongtian Zhang, Xiaofei Wang, Lanjun Wang, Xin Wang:
MetaEformer: Unveiling and Leveraging Meta-Patterns for Complex and Dynamic Systems Load Forecasting. 991-1002 - Yiqian Huang, Shiqi Zhang, Xiaokui Xiao:
KET-RAG: A Cost-Efficient Multi-Granular Indexing Framework for Graph-RAG. 1003-1012 - Makoto Imamura:
Generalized Discords for Time Series Anomaly Detection with Flexible Subsequence Lengths. 1013-1024 - Kazuki Ishikawa, Ryota Ozaki, Yohei Kanzaki, Ichiro Takeuchi, Masayuki Karasuyama:
Bayesian Optimization for Simultaneous Selection of Machine Learning Algorithms and Hyperparameters on Shared Latent Space. 1025-1036 - Hyunsik Jeon, Satoshi Koide, Yu Wang, Zhankui He, Julian J. McAuley:
Adapting Large Vision-Language Models to Visually-Aware Conversational Recommendation. 1037-1048 - Ju Jia, Jingxuan Yu, Di Wu, Cong Wu, Hengjie Zhu, Lina Wang:
Prompt as a Double-Edged Sword: A Dynamic Equilibrium Gradient-Assigned Attack against Graph Prompt Learning. 1049-1060 - Haiqi Jiang, Ying Ding, Chenjie Pan, Aimin Huang, Rui Chen, Chenyou Fan:
CMA: A Unified Contextual Meta-Adaptation Methodology for Time-Series Denoising and Prediction. 1061-1070 - Jiahui Jin, Yifan Song, Dong Kan, Haojia Zhu, Xiangguo Sun, Zhicheng Li, Xigang Sun, Jinghui Zhang:
Urban Region Pre-training and Prompting: A Graph-based Approach. 1071-1082 - Yilun Jin, Kun Zhu, Feng Tang, Jiaxuan Shi, Yong Chen:
Experience Speaks Louder: Black-box Hard-label Adversarial Attack through Reinforcement Learning. 1083-1093 - Clark Mingxuan Ju, Leonardo Neves, Bhuvesh Kumar, Liam Collins, Tong Zhao, Yuwei Qiu, Qing Dou, Sohail Nizam, Sen Yang, Neil Shah:
Revisiting Self-attention for Cross-domain Sequential Recommendation. 1094-1105 - Heesoo Jung, Chanyong Kim, Geonhee Han, Hogun Park:
Harnessing Influence Function in Explaining Graph Neural Networks. 1106-1117 - Noriaki Kawamae:
One-shot Multi-view Visual Conversational Recommendation. 1118-1127 - Noriaki Kawamae:
Knowledge-Aligned Domain Shift Tuning for Efficient Adaptation in Large Language Models. 1128-1138 - Duc Kieu, Kien Do, Toan Nguyen, Dang Nguyen, Thin Nguyen:
Bidirectional Diffusion Bridge Models. 1139-1148 - Junghun Kim, Hoyoung Yoon, Ka Hyun Park, U Kang:
Accurate Graph-based Multi-Positive Unlabeled Learning via Disentangled Multi-view Feature Propagation. 1149-1159 - Sein Kim, Hongseok Kang, Kibum Kim, Jiwan Kim, Donghyun Kim, Minchul Yang, Kwangjin Oh, Julian J. McAuley, Chanyoung Park:
Lost in Sequence: Do Large Language Models Understand Sequential Recommendation? 1160-1171 - Sejin Kim, Hosung Lee, Sundong Kim:
Addressing and Visualizing Misalignments in Human Task-Solving Trajectories. 1172-1183 - Taeri Kim, Sohee Ban, Hyunjoon Kim, Sang-Wook Kim:
STARLINE: Contrastive Learning with Modality-Aware Graph Refinement for Effective Multimedia Recommendation. 1184-1195 - Ricardo Knauer, Mario Koddenbrock, Raphael Wallsberger, Nicholas M. Brisson, Georg N. Duda, Deborah Falla, David W. Evans, Erik Rodner:
'Oh LLM, I'm Asking Thee, Please Give Me a Decision Tree': Zero-Shot Decision Tree Induction and Embedding with Large Language Models. 1196-1206 - Hector Kohler, Riad Akrour, Philippe Preux:
Breiman meets Bellman: Non-Greedy Decision Trees with MDPs. 1207-1218 - Meera Krishnamoorthy, Michael W. Sjoding, Jenna Wiens:
Cross-Validation for Longitudinal Datasets with Unstable Correlations. 1219-1228 - Yurui Lai, Taiyan Zhang, Renchi Yang:
Simple yet Effective Graph Distillation via Clustering. 1229-1240 - Jian Lang, Rongpei Hong, Zhangtao Cheng, Ting Zhong, Yong Wang, Fan Zhou:
REDEEMing Modality Information Loss: Retrieval-Guided Conditional Generation for Severely Modality Missing Learning. 1241-1252 - Junhyun Lee, Veronika Thost, Bumsoo Kim, Jaewoo Kang, Tengfei Ma:
Understanding and Tackling Over-Dilution in Graph Neural Networks. 1253-1261 - Kyungeun Lee, Moonjung Eo, Hye-Seung Cho, Min-Kook Suh, Seoyoon Kim, Ye Seul Sim, Suhee Yoon, Sanghyu Yoon, Woohyung Lim:
Range-limited Augmentation for Few-shot Learning in Tabular Data with Comprehensive Benchmark. 1262-1273 - Seung-eon Lee, Soopil Kim, Sion An, Sang-Chul Lee, Sang Hyun Park:
Logical Anomaly Detection with Text-based Logic via Component-Aware Contrastive Language-Image Training. 1274-1285 - Han Lei, Jiaxing Xu, Xia Dong, Yiping Ke:
Divergent Paths: Separating Homophilic and Heterophilic Learning for Enhanced Graph-level Representations. 1286-1295 - Runze Lei, Pinghui Wang, Juxiang Zeng, Chenxu Wang, Hongbin Pei, Junzhou Zhao:
PARSIFAL: Private and Robust Sign Federated Learning. 1296-1307 - Bingheng Li, Zhikai Chen, Haoyu Han, Shenglai Zeng, Jingzhe Liu, Jiliang Tang:
Unveiling Mode Connectivity in Graph Neural Network. 1308-1317 - Chenjie Li, Amir Gilad, Boris Glavic, Zhengjie Miao, Sudeepa Roy:
Refining Labeling Functions with Limited Labeled Data. 1318-1329 - Daixun Li, Weiying Xie, Mingxiang Cao, Yunke Wang, Yusi Zhang, Leyuan Fang, Yunsong Li, Chang Xu:
FusionSAM: Visual Multi-Modal Learning with Segment Anything Model. 1330-1340 - Gaotang Li, Danai Koutra, Yujun Yan:
Tackling Size Generalization of Graph Neural Networks on Biological Data from a Spectral Perspective. 1341-1352 - Guoming Li, Jian Yang, Yifan Chen:
Partition-wise Graph Filtering: A Unified Perspective Through the Lens of Graph Coarsening. 1353-1364 - Honghao Li, Yiwen Zhang, Yi Zhang, Lei Sang, Jieming Zhu:
Revisiting Feature Interactions from the Perspective of Quadratic Neural Networks for Click-through Rate Prediction. 1365-1375 - Jian Li, Han Wan, Ning Lin, Yu-Liang Zhan, Ruizhi Chengze, Haining Wang, Yi Zhang, Hongsheng Liu, Zidong Wang, Fan Yu, Hao Sun:
SlotPi: Physics-informed Object-centric Reasoning Models. 1376-1387 - Jinning Li, Ruipeng Han, Jingying Zeng, Dachun Sun, Chenkai Sun, Hanghang Tong, ChengXiang Zhai, Boleslaw K. Szymanski, Tarek F. Abdelzaher:
Learning to Slice: Self-Supervised Interpretable Hierarchical Representation Learning with Graph Auto-Encoder Tree. 1388-1399 - Junjun Li, Zeyuan Ma, Ting Huang, Yue-Jiao Gong:
Learn to Refine: Synergistic Multi-Agent Path Optimization for Lifelong Conflict-Free Navigation of Autonomous Vehicles. 1400-1411 - Juren Li, Yang Yang, Hanchen Su, Jiayu Liu, Youmin Chen, Jianfeng Zhang, Lujia Pan:
LiPM: Foundation Model for Lithium-Ion Battery Analysis. 1412-1423 - Ke Li, Lisi Chen, Shuo Shang, Christian S. Jensen, Panos Kalnis:
Beyond Locations: A Motion Range-Aware Similarity Join. 1424-1434
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