| 2024 | "Are Adversarial Phishing Webpages a Threat in Reality?" Understanding the Users' Perception of Adversarial Webpages. Ying Yuan, Qingying Hao, Giovanni Apruzzese, Mauro Conti, Gang Wang |
| 2024 | (In)Security of File Uploads in Node.js. Harun Oz, Abbas Acar, Ahmet Aris, Güliz Seray Tuncay, Amin Kharraz, A. Selcuk Uluagac |
| 2024 | A Counterfactual Framework for Learning and Evaluating Explanations for Recommender Systems. Oren Barkan, Veronika Bogina, Liya Gurevitch, Yuval Asher, Noam Koenigstein |
| 2024 | A Cross Domain Method for Customer Lifetime Value Prediction in Supply Chain Platform. Zhiyuan Zhou, Li Lin, Hai Wang, Xiaolei Zhou, Gong Wei, Shuai Wang |
| 2024 | A Data-Centric Multi-Objective Learning Framework for Responsible Recommendation Systems. Xu Huang, Jianxun Lian, Hao Wang, Hao Liao, Defu Lian, Xing Xie |
| 2024 | A Fast Hop-Biased Approximation Algorithm for the Quadratic Group Steiner Tree Problem. Xiaoqing Wang, Gong Cheng |
| 2024 | A Fast Similarity Matrix Calibration Method with Incomplete Query. Changyi Ma, Runsheng Yu, Youzhi Zhang |
| 2024 | A Knowledge-Injected Curriculum Pretraining Framework for Question Answering. Xin Lin, Tianhuang Su, Zhenya Huang, Shangzi Xue, Haifeng Liu, Enhong Chen |
| 2024 | A Method for Assessing Inference Patterns Captured by Embedding Models in Knowledge Graphs. Narayanan Asuri Krishnan, Carlos R. Rivero |
| 2024 | A Multifaceted Look at Starlink Performance. Nitinder Mohan, Andrew E. Ferguson, Hendrik Cech, Rohan Bose, Prakita Rayyan Renatin, Mahesh K. Marina, Jörg Ott |
| 2024 | A Quasi-Wasserstein Loss for Learning Graph Neural Networks. Minjie Cheng, Hongteng Xu |
| 2024 | A Similarity-based Approach for Efficient Large Quasi-clique Detection. Jiayang Pang, Chenhao Ma, Yixiang Fang |
| 2024 | A Simple but Effective Approach for Unsupervised Few-Shot Graph Classification. Yonghao Liu, Lan Huang, Bowen Cao, Ximing Li, Fausto Giunchiglia, Xiaoyue Feng, Renchu Guan |
| 2024 | A Study of GDPR Compliance under the Transparency and Consent Framework. Michael Smith, Antonio Torres-Agüero, Riley Grossman, Pritam Sen, Yi Chen, Cristian Borcea |
| 2024 | A Symbolic Rule Integration Framework with Logic Transformer for Inductive Relation Prediction. Yudai Pan, Jun Liu, Tianzhe Zhao, Lingling Zhang, Yun Lin, Jin Song Dong |
| 2024 | A Worldwide View on the Reachability of Encrypted DNS Services. Ruixuan Li, Baojun Liu, Chaoyi Lu, Haixin Duan, Jun Shao |
| 2024 | AI Deepfakes on the Web: The 'Wicked' Challenges for AI Ethics, Law and Technology. Jeannie Marie Paterson |
| 2024 | AI for Materials Innovation: Self-Improving Photosensitizer Discovery System via Bayesian Search with First-Principles Simulation. Bin Liu |
| 2024 | AN-Net: an Anti-Noise Network for Anonymous Traffic Classification. Xianwen Deng, Yijun Wang, Zhi Xue |
| 2024 | APT-Pipe: A Prompt-Tuning Tool for Social Data Annotation using ChatGPT. Yiming Zhu, Zhizhuo Yin, Gareth Tyson, Ehsan ul Haq, Lik-Hang Lee, Pan Hui |
| 2024 | ARES: Predictable Traffic Engineering under Controller Failures in SD-WANs. Songshi Dou, Li Qi, Zehua Guo |
| 2024 | ARTEMIS: Detecting Airdrop Hunters in NFT Markets with a Graph Learning System. Chenyu Zhou, Hongzhou Chen, Hao Wu, Junyu Zhang, Wei Cai |
| 2024 | Accelerating the Decentralized Federated Learning via Manipulating Edges. Mingyang Zhou, Gang Liu, Kezhong Lu, Rui Mao, Hao Liao |
| 2024 | Ad vs Organic: Revisiting Incentive Compatible Mechanism Design in E-commerce Platforms. Ningyuan Li, Yunxuan Ma, Yang Zhao, Qian Wang, Zhilin Zhang, Chuan Yu, Jian Xu, Bo Zheng, Xiaotie Deng |
| 2024 | AdFlush: A Real-World Deployable Machine Learning Solution for Effective Advertisement and Web Tracker Prevention. Kiho Lee, Chaejin Lim, Beomjin Jin, TaeYoung Kim, Hyoungshick Kim |
| 2024 | Adaptive Neural Ranking Framework: Toward Maximized Business Goal for Cascade Ranking Systems. Yunli Wang, Zhiqiang Wang, Jian Yang, Shiyang Wen, Dongying Kong, Han Li, Kun Gai |
| 2024 | Advancing Web 3.0: Making Smart Contracts Smarter on Blockchain. Junqin Huang, Linghe Kong, Guanjie Cheng, Qiao Xiang, Guihai Chen, Gang Huang, Xue Liu |
| 2024 | Adversarial Mask Explainer for Graph Neural Networks. Wei Zhang, Xiaofan Li, Wolfgang Nejdl |
| 2024 | Adversarial-Enhanced Causal Multi-Task Framework for Debiasing Post-Click Conversion Rate Estimation. Xinyue Zhang, Cong Huang, Kun Zheng, Hongzu Su, Tianxu Ji, Wei Wang, Hongkai Qi, Jingjing Li |
| 2024 | AgentCF: Collaborative Learning with Autonomous Language Agents for Recommender Systems. Junjie Zhang, Yupeng Hou, Ruobing Xie, Wenqi Sun, Julian J. McAuley, Wayne Xin Zhao, Leyu Lin, Ji-Rong Wen |
| 2024 | Air-CAD: Edge-Assisted Multi-Drone Network for Real-time Crowd Anomaly Detection. Yuanzheng Tan, Qing Li, Junkun Peng, Zhenhui Yuan, Yong Jiang |
| 2024 | Aligning Out-of-Distribution Web Images and Caption Semantics via Evidential Learning. Guohao Sun, Yue Bai, Xueying Yang, Yi Fang, Yun Fu, Zhiqiang Tao |
| 2024 | An Efficient Automatic Meta-Path Selection for Social Event Detection via Hyperbolic Space. Zitai Qiu, Congbo Ma, Jia Wu, Jian Yang |
| 2024 | An In-depth Investigation of User Response Simulation for Conversational Search. Zhenduo Wang, Zhichao Xu, Vivek Srikumar, Qingyao Ai |
| 2024 | Analysis and Detection of "Pink Slime" Websites in Social Media Posts. Abdullah Aljebreen, Weiyi Meng, Eduard C. Dragut |
| 2024 | Analyzing Ad Exposure and Content in Child-Oriented Videos on YouTube. Emaan Bilal Khan, Nida Tanveer, Aima Shahid, Mohammad Jaffer Iqbal, Haashim Ali Mirza, Armish Javed, Ihsan Ayyub Qazi, Zafar Ayyub Qazi |
| 2024 | Asking Multimodal Clarifying Questions in Mixed-Initiative Conversational Search. Yifei Yuan, Clemencia Siro, Mohammad Aliannejadi, Maarten de Rijke, Wai Lam |
| 2024 | Author Name Disambiguation via Paper Association Refinement and Compositional Contrastive Embedding. Dezhi Liu, Richong Zhang, Junfan Chen, Xinyue Chen |
| 2024 | Automating Website Registration for Studying GDPR Compliance. Karel Kubicek, Jakob Merane, Ahmed Bouhoula, David A. Basin |
| 2024 | BOND: Bootstrapping From-Scratch Name Disambiguation with Multi-task Promoting. Yuqing Cheng, Bo Chen, Fanjin Zhang, Jie Tang |
| 2024 | Back to the Future: Towards Explainable Temporal Reasoning with Large Language Models. Chenhan Yuan, Qianqian Xie, Jimin Huang, Sophia Ananiadou |
| 2024 | Barter Exchange with Shared Item Valuations. Juan Luque, Sharmila Duppala, John P. Dickerson, Aravind Srinivasan |
| 2024 | Bayesian Iterative Prediction and Lexical-based Interpretation for Disturbed Chinese Sentence Pair Matching. Muzhe Guo, Muhao Guo, Juntao Su, Junyu Chen, Jiaqian Yu, Jiaqi Wang, Hongfei Du, Parmanand Sahu, Ashwin Assysh Sharma, Fang Jin |
| 2024 | Benchmark and Neural Architecture for Conversational Entity Retrieval from a Knowledge Graph. Mona Zamiri, Yao Qiang, Fedor Nikolaev, Dongxiao Zhu, Alexander Kotov |
| 2024 | Best of Three Worlds: Adaptive Experimentation for Digital Marketing in Practice. Tanner Fiez, Houssam Nassif, Yu-Cheng Chen, Sergio Gamez, Lalit Jain |
| 2024 | Better to Ask in English: Cross-Lingual Evaluation of Large Language Models for Healthcare Queries. Yiqiao Jin, Mohit Chandra, Gaurav Verma, Yibo Hu, Munmun De Choudhury, Srijan Kumar |
| 2024 | Beyond Labels and Topics: Discovering Causal Relationships in Neural Topic Modeling. Yi-Kun Tang, Heyan Huang, Xuewen Shi, Xian-Ling Mao |
| 2024 | Bidder Selection Problem in Position Auctions: A Fast and Simple Algorithm via Poisson Approximation. Nikolai Gravin, Yixuan Even Xu, Renfei Zhou |
| 2024 | Bit-mask Robust Contrastive Knowledge Distillation for Unsupervised Semantic Hashing. Liyang He, Zhenya Huang, Jiayu Liu, Enhong Chen, Fei Wang, Jing Sha, Shijin Wang |
| 2024 | BlockDFL: A Blockchain-based Fully Decentralized Peer-to-Peer Federated Learning Framework. Zhen Qin, Xueqiang Yan, MengChu Zhou, Shuiguang Deng |
| 2024 | Blockchain Censorship. Anton Wahrstätter, Jens Ernstberger, Aviv Yaish, Liyi Zhou, Kaihua Qin, Taro Tsuchiya, Sebastian Steinhorst, Davor Svetinovic, Nicolas Christin, Mikolaj Barczentewicz, Arthur Gervais |
| 2024 | Bots, Elections, and Controversies: Twitter Insights from Brazil's Polarised Elections. Diogo Pacheco |
| 2024 | Breaking the Time-Frequency Granularity Discrepancy in Time-Series Anomaly Detection. Youngeun Nam, Susik Yoon, Yooju Shin, Minyoung Bae, Hwanjun Song, Jae-Gil Lee, Byung Suk Lee |
| 2024 | Breaking the Trilemma of Privacy, Utility, and Efficiency via Controllable Machine Unlearning. Zheyuan Liu, Guangyao Dou, Eli Chien, Chunhui Zhang, Yijun Tian, Ziwei Zhu |
| 2024 | Bridging or Breaking: Impact of Intergroup Interactions on Religious Polarization. Rochana Chaturvedi, Sugat Chaturvedi, Elena Zheleva |
| 2024 | Bridging the Space Gap: Unifying Geometry Knowledge Graph Embedding with Optimal Transport. Yuhan Liu, Zelin Cao, Xing Gao, Ji Zhang, Rui Yan |
| 2024 | Budget-Constrained Auctions with Unassured Priors: Strategic Equivalence and Structural Properties. Zhaohua Chen, Mingwei Yang, Chang Wang, Jicheng Li, Zheng Cai, Yukun Ren, Zhihua Zhu, Xiaotie Deng |
| 2024 | COLA: Cross-city Mobility Transformer for Human Trajectory Simulation. Yu Wang, Tongya Zheng, Yuxuan Liang, Shunyu Liu, Mingli Song |
| 2024 | Calibrating Graph Neural Networks from a Data-centric Perspective. Cheng Yang, Chengdong Yang, Chuan Shi, Yawen Li, Zhiqiang Zhang, Jun Zhou |
| 2024 | Can GNN be Good Adapter for LLMs? Xuanwen Huang, Kaiqiao Han, Yang Yang, Dezheng Bao, Quanjin Tao, Ziwei Chai, Qi Zhu |
| 2024 | Can One Embedding Fit All? A Multi-Interest Learning Paradigm Towards Improving User Interest Diversity Fairness. Yuying Zhao, Minghua Xu, Huiyuan Chen, Yuzhong Chen, Yiwei Cai, Rashidul Islam, Yu Wang, Tyler Derr |
| 2024 | Can Small Language Models be Good Reasoners for Sequential Recommendation? Yuling Wang, Changxin Tian, Binbin Hu, Yanhua Yu, Ziqi Liu, Zhiqiang Zhang, Jun Zhou, Liang Pang, Xiao Wang |
| 2024 | CapAlign: Improving Cross Modal Alignment via Informative Captioning for Harmful Meme Detection. Junhui Ji, Xuanrui Lin, Usman Naseem |
| 2024 | Cardinality Counting in "Alcatraz": A Privacy-aware Federated Learning Approach. Nan Wu, Xin Yuan, Shuo Wang, Hongsheng Hu, Minhui Xue |
| 2024 | Category-based and Popularity-guided Video Game Recommendation: A Balance-oriented Framework. Xiping Li, Jianghong Ma, Kangzhe Liu, Shanshan Feng, Haijun Zhang, Yutong Wang |
| 2024 | Causal Graph ODE: Continuous Treatment Effect Modeling in Multi-agent Dynamical Systems. Zijie Huang, Jeehyun Hwang, Junkai Zhang, Jinwoo Baik, Weitong Zhang, Dominik Wodarz, Yizhou Sun, Quanquan Gu, Wei Wang |
| 2024 | Causal Question Answering with Reinforcement Learning. Lukas Blübaum, Stefan Heindorf |
| 2024 | Causally Debiased Time-aware Recommendation. Lei Wang, Chen Ma, Xian Wu, Zhaopeng Qiu, Yefeng Zheng, Xu Chen |
| 2024 | Challenges Toward AGI and Its Impact to the Web. Bo Zhang, Jie Tang |
| 2024 | Challenging Low Homophily in Social Recommendation. Wei Jiang, Xinyi Gao, Guandong Xu, Tong Chen, Hongzhi Yin |
| 2024 | Characterizing Ethereum Upgradable Smart Contracts and Their Security Implications. Xiaofan Li, Jin Yang, Jiaqi Chen, Yuzhe Tang, Xing Gao |
| 2024 | ClickPrompt: CTR Models are Strong Prompt Generators for Adapting Language Models to CTR Prediction. Jianghao Lin, Bo Chen, Hangyu Wang, Yunjia Xi, Yanru Qu, Xinyi Dai, Kangning Zhang, Ruiming Tang, Yong Yu, Weinan Zhang |
| 2024 | Clickbait vs. Quality: How Engagement-Based Optimization Shapes the Content Landscape in Online Platforms. Nicole Immorlica, Meena Jagadeesan, Brendan Lucier |
| 2024 | Co-clustering for Federated Recommender System. Xinrui He, Shuo Liu, Jacky Keung, Jingrui He |
| 2024 | Cognitive Personalized Search Integrating Large Language Models with an Efficient Memory Mechanism. Yujia Zhou, Qiannan Zhu, Jiajie Jin, Zhicheng Dou |
| 2024 | Cold Start or Hot Start? Robust Slow Start in Congestion Control with A Priori Knowledge for Mobile Web Services. Jia Zhang, Haixuan Tong, Enhuan Dong, Xin Qian, Mingwei Xu, Xiaotian Li, Zili Meng |
| 2024 | Cold-start Bundle Recommendation via Popularity-based Coalescence and Curriculum Heating. Hyunsik Jeon, Jong-eun Lee, Jeongin Yun, U Kang |
| 2024 | Collaborate to Adapt: Source-Free Graph Domain Adaptation via Bi-directional Adaptation. Zhen Zhang, Meihan Liu, Anhui Wang, Hongyang Chen, Zhao Li, Jiajun Bu, Bingsheng He |
| 2024 | Collaboration-Aware Hybrid Learning for Knowledge Development Prediction. Liyi Chen, Chuan Qin, Ying Sun, Xin Song, Tong Xu, Hengshu Zhu, Hui Xiong |
| 2024 | Collaborative Large Language Model for Recommender Systems. Yaochen Zhu, Liang Wu, Qi Guo, Liangjie Hong, Jundong Li |
| 2024 | Collaborative Metapath Enhanced Corporate Default Risk Assessment on Heterogeneous Graph. Zheng Zhang, Yingsheng Ji, Jiachen Shen, Yushu Chen, Xi Zhang, Guangwen Yang |
| 2024 | Consistency Guided Knowledge Retrieval and Denoising in LLMs for Zero-shot Document-level Relation Triplet Extraction. Qi Sun, Kun Huang, Xiaocui Yang, Rong Tong, Kun Zhang, Soujanya Poria |
| 2024 | Content Moderation and the Formation of Online Communities: A Theoretical Framework. Cynthia Dwork, Chris Hays, Jon M. Kleinberg, Manish Raghavan |
| 2024 | ContraMTD: An Unsupervised Malicious Network Traffic Detection Method based on Contrastive Learning. Xueying Han, Susu Cui, Jian Qin, Song Liu, Bo Jiang, Cong Dong, Zhigang Lu, Baoxu Liu |
| 2024 | Contrastive Fingerprinting: A Novel Website Fingerprinting Attack over Few-shot Traces. Yi Xie, Jiahao Feng, Wenju Huang, Yixi Zhang, Xueliang Sun, Xiaochou Chen, Xiapu Luo |
| 2024 | Contrastive Learning for Multimodal Classification of Crisis related Tweets. Bishwas Mandal, Sarthak Khanal, Doina Caragea |
| 2024 | Cooperative Classification and Rationalization for Graph Generalization. Linan Yue, Qi Liu, Ye Liu, Weibo Gao, Fangzhou Yao, Wenfeng Li |
| 2024 | Core-Competitiveness in Partially Observable Networked Market. Bin Li, Dong Hao |
| 2024 | Cost-effective Data Labelling for Graph Neural Networks. Shixun Huang, Ge Lee, Zhifeng Bao, Shirui Pan |
| 2024 | Could Small Language Models Serve as Recommenders? Towards Data-centric Cold-start Recommendation. Xuansheng Wu, Huachi Zhou, Yucheng Shi, Wenlin Yao, Xiao Huang, Ninghao Liu |
| 2024 | Cross-Space Adaptive Filter: Integrating Graph Topology and Node Attributes for Alleviating the Over-smoothing Problem. Chen Huang, Haoyang Li, Yifan Zhang, Wenqiang Lei, Jiancheng Lv |
| 2024 | DPAR: Decoupled Graph Neural Networks with Node-Level Differential Privacy. Qiuchen Zhang, Hong-Kyu Lee, Jing Ma, Jian Lou, Carl Yang, Li Xiong |
| 2024 | DRAM-like Architecture with Asynchronous Refreshing for Continual Relation Extraction. Tianci Bu, Kang Yang, Wenchuan Yang, Jiawei Feng, Xiaoyu Zhang, Xin Lu |
| 2024 | DSLR: Diversity Enhancement and Structure Learning for Rehearsal-based Graph Continual Learning. Seungyoon Choi, Wonjoong Kim, Sungwon Kim, Yeonjun In, Sein Kim, Chanyoung Park |
| 2024 | Data Exchange Markets via Utility Balancing. Aditya Bhaskara, Sreenivas Gollapudi, Sungjin Im, Kostas Kollias, Kamesh Munagala, Govind S. Sankar |
| 2024 | Debiasing Recommendation with Personal Popularity. Wentao Ning, Reynold Cheng, Xiao Yan, Ben Kao, Nan Huo, Nur Al Hasan Haldar, Bo Tang |
| 2024 | Decentralized Collaborative Learning with Adaptive Reference Data for On-Device POI Recommendation. Ruiqi Zheng, Liang Qu, Tong Chen, Lizhen Cui, Yuhui Shi, Hongzhi Yin |
| 2024 | Decoupled Variational Graph Autoencoder for Link Prediction. Yoon-Sik Cho |
| 2024 | Deliberate Exposure to Opposing Views and Its Association with Behavior and Rewards on Political Communities. Alexandros Efstratiou |
| 2024 | DenseFlow: Spotting Cryptocurrency Money Laundering in Ethereum Transaction Graphs. Dan Lin, Jiajing Wu, Yunmei Yu, Qishuang Fu, Zibin Zheng, Changlin Yang |
| 2024 | Densest Subhypergraph: Negative Supermodular Functions and Strongly Localized Methods. Yufan Huang, David F. Gleich, Nate Veldt |
| 2024 | Descriptive Kernel Convolution Network with Improved Random Walk Kernel. Meng-Chieh Lee, Lingxiao Zhao, Leman Akoglu |
| 2024 | Detecting Illicit Food Factories from Chemical Declaration Data via Graph-aware Self-supervised Contrastive Anomaly Ranking. Sheng-Fang Yang, Cheng-Te Li |
| 2024 | Detecting and Understanding Self-Deleting JavaScript Code. Xinzhe Wang, Zeyang Zhuang, Wei Meng, James Cheng |
| 2024 | Diagrammatic Reasoning for ALC Visualization with Logic Graphs. Ildar Baimuratov |
| 2024 | Differentially Private Selection from Secure Distributed Computing. Ivan Damgård, Hannah Keller, Boel Nelson, Claudio Orlandi, Rasmus Pagh |
| 2024 | Diffusion-based Negative Sampling on Graphs for Link Prediction. Trung-Kien Nguyen, Yuan Fang |
| 2024 | DirectFaaS: A Clean-Slate Network Architecture for Efficient Serverless Chain Communications. Qingyang Zeng, Kaiyu Hou, Xue Leng, Yan Chen |
| 2024 | Disambiguated Node Classification with Graph Neural Networks. Tianxiang Zhao, Xiang Zhang, Suhang Wang |
| 2024 | Discovering and Measuring CDNs Prone to Domain Fronting. Karthika Subramani, Roberto Perdisci, Pierros-Christos Skafidas, Manos Antonakakis |
| 2024 | Distributed Data Placement and Content Delivery in Web Caches with Non-Metric Access Costs. S. Rasoul Etesami |
| 2024 | Distributionally Robust Graph-based Recommendation System. Bohao Wang, Jiawei Chen, Changdong Li, Sheng Zhou, Qihao Shi, Yang Gao, Yan Feng, Chun Chen, Can Wang |
| 2024 | Divide, Conquer, and Coalesce: Meta Parallel Graph Neural Network for IoT Intrusion Detection at Scale. Hua Ding, Lixing Chen, Shenghong Li, Yang Bai, Pan Zhou, Zhe Qu |
| 2024 | Don't Bite Off More than You Can Chew: Investigating Excessive Permission Requests in Trigger-Action Integrations. Liuhuo Wan, Kailong Wang, Kulani Mahadewa, Haoyu Wang, Guangdong Bai |
| 2024 | Doubly Calibrated Estimator for Recommendation on Data Missing Not at Random. Wonbin Kweon, Hwanjo Yu |
| 2024 | Dual Box Embeddings for the Description Logic EL Mathias Jackermeier, Jiaoyan Chen, Ian Horrocks |
| 2024 | DualCL: Principled Supervised Contrastive Learning as Mutual Information Maximization for Text Classification. Junfan Chen, Richong Zhang, Yaowei Zheng, Qianben Chen, Chunming Hu, Yongyi Mao |
| 2024 | Dynamic Graph Information Bottleneck. Haonan Yuan, Qingyun Sun, Xingcheng Fu, Cheng Ji, Jianxin Li |
| 2024 | Dynamic Multi-Network Mining of Tensor Time Series. Kohei Obata, Koki Kawabata, Yasuko Matsubara, Yasushi Sakurai |
| 2024 | E2Usd: Efficient-yet-effective Unsupervised State Detection for Multivariate Time Series. Zhichen Lai, Huan Li, Dalin Zhang, Yan Zhao, Weizhu Qian, Christian S. Jensen |
| 2024 | ESCNet: Entity-enhanced and Stance Checking Network for Multi-modal Fact-Checking. Fanrui Zhang, Jiawei Liu, Jingyi Xie, Qiang Zhang, Yongchao Xu, Zheng-Jun Zha |
| 2024 | EXGC: Bridging Efficiency and Explainability in Graph Condensation. Junfeng Fang, Xinglin Li, Yongduo Sui, Yuan Gao, Guibin Zhang, Kun Wang, Xiang Wang, Xiangnan He |
| 2024 | Efficiency of Non-Truthful Auctions in Auto-bidding with Budget Constraints. Christopher Liaw, Aranyak Mehta, Wennan Zhu |
| 2024 | Efficiency of the Generalized Second-Price Auction for Value Maximizers. Yuan Deng, Mohammad Mahdian, Jieming Mao, Vahab Mirrokni, Hanrui Zhang, Song Zuo |
| 2024 | Efficient Computation for Diagonal of Forest Matrix via Variance-Reduced Forest Sampling. Haoxin Sun, Zhongzhi Zhang |
| 2024 | Efficient Computation of Signature-Restricted Views for Semantic Web Ontologies. Yizheng Zhao |
| 2024 | Efficient Exact and Approximate Betweenness Centrality Computation for Temporal Graphs. Tianming Zhang, Yunjun Gao, Jie Zhao, Lu Chen, Lu Jin, Zhengyi Yang, Bin Cao, Jing Fan |
| 2024 | Efficient Noise-Decoupling for Multi-Behavior Sequential Recommendation. Yongqiang Han, Hao Wang, Kefan Wang, Likang Wu, Zhi Li, Wei Guo, Yong Liu, Defu Lian, Enhong Chen |
| 2024 | Endowing Pre-trained Graph Models with Provable Fairness. Zhongjian Zhang, Mengmei Zhang, Yue Yu, Cheng Yang, Jiawei Liu, Chuan Shi |
| 2024 | Enhancing Complex Question Answering over Knowledge Graphs through Evidence Pattern Retrieval. Wentao Ding, Jinmao Li, Liangchuan Luo, Yuzhong Qu |
| 2024 | Enhancing Fairness in Meta-learned User Modeling via Adaptive Sampling. Zheng Zhang, Qi Liu, Zirui Hu, Yi Zhan, Zhenya Huang, Weibo Gao, Qingyang Mao |
| 2024 | Enhancing Recommendation Accuracy and Diversity with Box Embedding: A Universal Framework. Cheng Wu, Shaoyun Shi, Chaokun Wang, Ziyang Liu, Wang Peng, Wenjin Wu, Dongying Kong, Han Li, Kun Gai |
| 2024 | Ensuring User-side Fairness in Dynamic Recommender Systems. Hyunsik Yoo, Zhichen Zeng, Jian Kang, Ruizhong Qiu, David Zhou, Zhining Liu, Fei Wang, Charlie Xu, Eunice Chan, Hanghang Tong |
| 2024 | Entity Disambiguation with Extreme Multi-label Ranking. Jyun-Yu Jiang, Wei-Cheng Chang, Jiong Zhang, Cho-Jui Hsieh, Hsiang-Fu Yu |
| 2024 | Euphemism Identification via Feature Fusion and Individualization. Yuxue Hu, Mingmin Wu, Zhongqiang Huang, Junsong Li, Xing Ge, Ying Sha |
| 2024 | Exit Ripple Effects: Understanding the Disruption of Socialization Networks Following Employee Departures. David Gamba, Yulin Yu, Yuan Yuan, Grant Schoenebeck, Daniel M. Romero |
| 2024 | Experimental Security Analysis of Sensitive Data Access by Browser Extensions. Asmit Nayak, Rishabh Khandelwal, Earlence Fernandes, Kassem Fawaz |
| 2024 | Explainable Fake News Detection with Large Language Model via Defense Among Competing Wisdom. Bo Wang, Jing Ma, Hongzhan Lin, Zhiwei Yang, Ruichao Yang, Yuan Tian, Yi Chang |
| 2024 | Exploring Neural Scaling Law and Data Pruning Methods For Node Classification on Large-scale Graphs. Zhen Wang, Yaliang Li, Bolin Ding, Yule Li, Zhewei Wei |
| 2024 | Exploring Unconfirmed Transactions for Effective Bitcoin Address Clustering. Kai Wang, Yakun Cheng, Michael Wen Tong, Zhenghao Niu, Jun Pang, Weili Han |
| 2024 | Extracting Small Subgraphs in Road Networks. Sara Ahmadian, Sreenivas Gollapudi, Gregory Hutchins, Kostas Kollias, Xizhi Tan |
| 2024 | Fact Embedding through Diffusion Model for Knowledge Graph Completion. Xiao Long, Liansheng Zhuang, Aodi Li, Houqiang Li, Shafei Wang |
| 2024 | Fair Graph Representation Learning via Sensitive Attribute Disentanglement. Yuchang Zhu, Jintang Li, Zibin Zheng, Liang Chen |
| 2024 | Fair Surveillance Assignment Problem. Fangxiao Wang, Bo Li |
| 2024 | FairSync: Ensuring Amortized Group Exposure in Distributed Recommendation Retrieval. Chen Xu, Jun Xu, Yiming Ding, Xiao Zhang, Qi Qi |
| 2024 | Fairness Rising from the Ranks: HITS and PageRank on Homophilic Networks. Ana-Andreea Stoica, Nelly Litvak, Augustin Chaintreau |
| 2024 | Faithful Temporal Question Answering over Heterogeneous Sources. Zhen Jia, Philipp Christmann, Gerhard Weikum |
| 2024 | Fake Resume Attacks: Data Poisoning on Online Job Platforms. Michiharu Yamashita, Thanh Tran, Dongwon Lee |
| 2024 | Fast Graph Condensation with Structure-based Neural Tangent Kernel. Lin Wang, Wenqi Fan, Jiatong Li, Yao Ma, Qing Li |
| 2024 | Fast Inference of Removal-Based Node Influence. Weikai Li, Zhiping Xiao, Xiao Luo, Yizhou Sun |
| 2024 | Fast and Accurate Fair k-Center Clustering in Doubling Metrics. Matteo Ceccarello, Andrea Pietracaprina, Geppino Pucci |
| 2024 | FedDSE: Distribution-aware Sub-model Extraction for Federated Learning over Resource-constrained Devices. Haozhao Wang, Yabo Jia, Meng Zhang, Qinghao Hu, Hao Ren, Peng Sun, Yonggang Wen, Tianwei Zhang |
| 2024 | FedUP: Querying Large-Scale Federations of SPARQL Endpoints. Julien Aimonier-Davat, Brice Nédelec, Minh Hoang Dang, Pascal Molli, Hala Skaf-Molli |
| 2024 | Federated Heterogeneous Graph Neural Network for Privacy-preserving Recommendation. Bo Yan, Yang Cao, Haoyu Wang, Wenchuan Yang, Junping Du, Chuan Shi |
| 2024 | Federated Learning Vulnerabilities: Privacy Attacks with Denoising Diffusion Probabilistic Models. Hongyan Gu, Xinyi Zhang, Jiang Li, Hui Wei, Baiqi Li, Xinli Huang |
| 2024 | Filter Bubble or Homogenization? Disentangling the Long-Term Effects of Recommendations on User Consumption Patterns. Md Sanzeed Anwar, Grant Schoenebeck, Paramveer S. Dhillon |
| 2024 | Finding Densest Subgraphs with Edge-Color Constraints. Lutz Oettershagen, Honglian Wang, Aristides Gionis |
| 2024 | Fine-Tuning Games: Bargaining and Adaptation for General-Purpose Models. Benjamin Laufer, Jon M. Kleinberg, Hoda Heidari |
| 2024 | Fingerprinting the Shadows: Unmasking Malicious Servers with Machine Learning-Powered TLS Analysis. Andreas Theofanous, Eva Papadogiannaki, Alexander Shevtsov, Sotiris Ioannidis |
| 2024 | Follow the Path: Hierarchy-Aware Extreme Multi-Label Completion for Semantic Text Tagging. Natalia Ostapuk, Julien Audiffren, Ljiljana Dolamic, Alain Mermoud, Philippe Cudré-Mauroux |
| 2024 | FreqMAE: Frequency-Aware Masked Autoencoder for Multi-Modal IoT Sensing. Denizhan Kara, Tomoyoshi Kimura, Shengzhong Liu, Jinyang Li, Dongxin Liu, Tianshi Wang, Ruijie Wang, Yizhuo Chen, Yigong Hu, Tarek F. Abdelzaher |
| 2024 | Friend or Foe? Mining Suspicious Behavior via Graph Capsule Infomax Detector against Fraudsters. Xiangping Zheng, Bo Wu, Xun Liang, Wei Li |
| 2024 | From Promises to Practice: Evaluating the Private Browsing Modes of Android Browser Apps. Xiaoyin Liu, Wenzhi Li, Qinsheng Hou, Shishuai Yang, Lingyun Ying, Wenrui Diao, Yanan Li, Shanqing Guo, Haixin Duan |
| 2024 | From Shapes to Shapes: Inferring SHACL Shapes for Results of SPARQL CONSTRUCT Queries. Philipp Seifer, Daniel Hernández, Ralf Lämmel, Steffen Staab |
| 2024 | Full Stage Learning to Rank: A Unified Framework for Multi-Stage Systems. Kai Zheng, Haijun Zhao, Rui Huang, Beichuan Zhang, Na Mou, Yanan Niu, Yang Song, Hongning Wang, Kun Gai |
| 2024 | Full-Attention Driven Graph Contrastive Learning: with Effective Mutual Information Insight. Long Li, Zemin Liu, Chenghao Liu, Jianling Sun |
| 2024 | Full-stage Diversified Recommendation: Large-scale Online Experiments in Short-video Platform. Nian Li, Yunzhu Pan, Chen Gao, Depeng Jin, Qingmin Liao |
| 2024 | FusionRender: Harnessing WebGPU's Power for Enhanced Graphics Performance on Web Browsers. Weichen Bi, Yun Ma, Yudong Han, Yifan Chen, Deyu Tian, Jiaqi Du |
| 2024 | GAMMA: Graph Neural Network-Based Multi-Bottleneck Localization for Microservices Applications. Gagan Somashekar, Anurag Dutt, Mainak Adak, Tania Lorido-Botran, Anshul Gandhi |
| 2024 | GAUSS: GrAph-customized Universal Self-Supervised Learning. Liang Yang, Weixiao Hu, Jizhong Xu, Runjie Shi, Dongxiao He, Chuan Wang, Xiaochun Cao, Zhen Wang, Bingxin Niu, Yuanfang Guo |
| 2024 | GEES: Enabling Location Privacy-Preserving Energy Saving in Multi-Access Edge Computing. Ziqi Wang, Xiaoyu Xia, Minhui Xue, Ibrahim Khalil, Minghui Liwang, Xun Yi |
| 2024 | GNNFingers: A Fingerprinting Framework for Verifying Ownerships of Graph Neural Networks. Xiaoyu You, Youhe Jiang, Jianwei Xu, Mi Zhang, Min Yang |
| 2024 | GNNShap: Scalable and Accurate GNN Explanation using Shapley Values. Selahattin Akkas, Ariful Azad |
| 2024 | GRASP: Hardening Serverless Applications through Graph Reachability Analysis of Security Policies. Isaac Polinsky, Pubali Datta, Adam Bates, William Enck |
| 2024 | Game-theoretic Counterfactual Explanation for Graph Neural Networks. Chirag Chhablani, Sarthak Jain, Akshay Channesh, Ian A. Kash, Sourav Medya |
| 2024 | General Debiasing for Graph-based Collaborative Filtering via Adversarial Graph Dropout. An Zhang, Wenchang Ma, Pengbo Wei, Leheng Sheng, Xiang Wang |
| 2024 | Generating Multi-turn Clarification for Web Information Seeking. Ziliang Zhao, Zhicheng Dou |
| 2024 | Generative News Recommendation. Shen Gao, Jiabao Fang, Quan Tu, Zhitao Yao, Zhumin Chen, Pengjie Ren, Zhaochun Ren |
| 2024 | Getting Bored of Cyberwar: Exploring the Role of Low-level Cybercrime Actors in the Russia-Ukraine Conflict. Anh V. Vu, Daniel R. Thomas, Ben Collier, Alice Hutchings, Richard Clayton, Ross J. Anderson |
| 2024 | Global News Synchrony and Diversity During the Start of the COVID-19 Pandemic. Xi Chen, Scott A. Hale, David Jurgens, Mattia Samory, Ethan Zuckerman, Przemyslaw A. Grabowicz |
| 2024 | Globally Interpretable Graph Learning via Distribution Matching. Yi Nian, Yurui Chang, Wei Jin, Lu Lin |
| 2024 | Graph Anomaly Detection with Bi-level Optimization. Yuan Gao, Junfeng Fang, Yongduo Sui, Yangyang Li, Xiang Wang, Huamin Feng, Yongdong Zhang |
| 2024 | Graph Contrastive Learning Meets Graph Meta Learning: A Unified Method for Few-shot Node Tasks. Hao Liu, Jiarui Feng, Lecheng Kong, Dacheng Tao, Yixin Chen, Muhan Zhang |
| 2024 | Graph Contrastive Learning Reimagined: Exploring Universality. Jiaming Zhuo, Can Cui, Kun Fu, Bingxin Niu, Dongxiao He, Chuan Wang, Yuanfang Guo, Zhen Wang, Xiaochun Cao, Liang Yang |
| 2024 | Graph Contrastive Learning via Interventional View Generation. Zengyi Wo, Minglai Shao, Wenjun Wang, Xuan Guo, Lu Lin |
| 2024 | Graph Contrastive Learning with Cohesive Subgraph Awareness. Yucheng Wu, Leye Wang, Xiao Han, Han-Jia Ye |
| 2024 | Graph Contrastive Learning with Kernel Dependence Maximization for Social Recommendation. Xuelian Ni, Fei Xiong, Yu Zheng, Liang Wang |
| 2024 | Graph Fairness Learning under Distribution Shifts. Yibo Li, Xiao Wang, Yujie Xing, Shaohua Fan, Ruijia Wang, Yaoqi Liu, Chuan Shi |
| 2024 | Graph Out-of-Distribution Generalization via Causal Intervention. Qitian Wu, Fan Nie, Chenxiao Yang, Tianyi Bao, Junchi Yan |
| 2024 | Graph Principal Flow Network for Conditional Graph Generation. Zhanfeng Mo, Tianze Luo, Sinno Jialin Pan |
| 2024 | Graph-Skeleton: ~1% Nodes are Sufficient to Represent Billion-Scale Graph. Linfeng Cao, Haoran Deng, Yang Yang, Chunping Wang, Lei Chen |
| 2024 | GraphControl: Adding Conditional Control to Universal Graph Pre-trained Models for Graph Domain Transfer Learning. Yun Zhu, Yaoke Wang, Haizhou Shi, Zhenshuo Zhang, Dian Jiao, Siliang Tang |
| 2024 | GraphLeak: Patient Record Leakage through Gradients with Knowledge Graph. Xi Sheryl Zhang, Weifan Guan, Jiahao Lu, Zhaopeng Qiu, Jian Cheng, Xian Wu, Yefeng Zheng |
| 2024 | GraphPro: Graph Pre-training and Prompt Learning for Recommendation. Yuhao Yang, Lianghao Xia, Da Luo, Kangyi Lin, Chao Huang |
| 2024 | GraphTranslator: Aligning Graph Model to Large Language Model for Open-ended Tasks. Mengmei Zhang, Mingwei Sun, Peng Wang, Shen Fan, Yanhu Mo, Xiaoxiao Xu, Hong Liu, Cheng Yang, Chuan Shi |
| 2024 | HD-KT: Advancing Robust Knowledge Tracing via Anomalous Learning Interaction Detection. Haiping Ma, Yong Yang, Chuan Qin, Xiaoshan Yu, Shangshang Yang, Xingyi Zhang, Hengshu Zhu |
| 2024 | HSDirSniper: A New Attack Exploiting Vulnerabilities in Tor's Hidden Service Directories. Qingfeng Zhang, Zhiyang Teng, Xuebin Wang, Yue Gao, Qingyun Liu, Jinqiao Shi |
| 2024 | HaSa: Hardness and Structure-Aware Contrastive Knowledge Graph Embedding. Honggen Zhang, June Zhang, Igor Molybog |
| 2024 | Harnessing Large Language Models for Text-Rich Sequential Recommendation. Zhi Zheng, Wenshuo Chao, Zhaopeng Qiu, Hengshu Zhu, Hui Xiong |
| 2024 | Harnessing Multi-Role Capabilities of Large Language Models for Open-Domain Question Answering. Hongda Sun, Yuxuan Liu, Chengwei Wu, Haiyu Yan, Cheng Tai, Xin Gao, Shuo Shang, Rui Yan |
| 2024 | Helen: Optimizing CTR Prediction Models with Frequency-wise Hessian Eigenvalue Regularization. Zirui Zhu, Yong Liu, Zangwei Zheng, Huifeng Guo, Yang You |
| 2024 | HetGPT: Harnessing the Power of Prompt Tuning in Pre-Trained Heterogeneous Graph Neural Networks. Yihong Ma, Ning Yan, Jiayu Li, Masood S. Mortazavi, Nitesh V. Chawla |
| 2024 | Heterogeneous Subgraph Transformer for Fake News Detection. Yuchen Zhang, Xiaoxiao Ma, Jia Wu, Jian Yang, Hao Fan |
| 2024 | Hierarchical Graph Signal Processing for Collaborative Filtering. Jiafeng Xia, Dongsheng Li, Hansu Gu, Tun Lu, Peng Zhang, Li Shang, Ning Gu |
| 2024 | Hierarchical Position Embedding of Graphs with Landmarks and Clustering for Link Prediction. Minsang Kim, Seung Baek |
| 2024 | High-Frequency-aware Hierarchical Contrastive Selective Coding for Representation Learning on Text Attributed Graphs. Peiyan Zhang, Chaozhuo Li, Liying Kang, Feiran Huang, Senzhang Wang, Xing Xie, Sunghun Kim |
| 2024 | How Contentious Terms About People and Cultures are Used in Linked Open Data. Andrei Nesterov, Laura Hollink, Jacco van Ossenbruggen |
| 2024 | How Few Davids Improve One Goliath: Federated Learning in Resource-Skewed Edge Computing Environments. Jiayun Zhang, Shuheng Li, Haiyu Huang, Zihan Wang, Xiaohan Fu, Dezhi Hong, Rajesh K. Gupta, Jingbo Shang |
| 2024 | Human vs ChatGPT: Effect of Data Annotation in Interpretable Crisis-Related Microblog Classification. Thi Huyen Nguyen, Koustav Rudra |
| 2024 | Hyperlink Hijacking: Exploiting Erroneous URL Links to Phantom Domains. Kevin Saric, Felix Savins, Gowri Sankar Ramachandran, Raja Jurdak, Surya Nepal |
| 2024 | IDEA-DAC: Integrity-Driven Editing for Accountable Decentralized Anonymous Credentials via ZK-JSON. Shuhao Zheng, Zonglun Li, Junliang Luo, Ziyue Xin, Xue Liu |
| 2024 | IME: Integrating Multi-curvature Shared and Specific Embedding for Temporal Knowledge Graph Completion. Jiapu Wang, Zheng Cui, Boyue Wang, Shirui Pan, Junbin Gao, Baocai Yin, Wen Gao |
| 2024 | Identifying Risky Vendors in Cryptocurrency P2P Marketplaces. Taro Tsuchiya, Alejandro Cuevas Villalba, Nicolas Christin |
| 2024 | Identifying VPN Servers through Graph-Represented Behaviors. Chenxu Wang, Jiangyi Yin, Zhao Li, Hongbo Xu, Zhongyi Zhang, Qingyun Liu |
| 2024 | Improving Item-side Fairness of Multimodal Recommendation via Modality Debiasing. Yu Shang, Chen Gao, Jiansheng Chen, Depeng Jin, Yong Li |
| 2024 | Improving Retrieval in Theme-specific Applications using a Corpus Topical Taxonomy. SeongKu Kang, Shivam Agarwal, Bowen Jin, Dongha Lee, Hwanjo Yu, Jiawei Han |
| 2024 | InArt: In-Network Aggregation with Route Selection for Accelerating Distributed Training. Jiawei Liu, Yutong Zhai, Gongming Zhao, Hongli Xu, Jin Fang, Zhen Zeng, Ying Zhu |
| 2024 | Incentive and Dynamic Client Selection for Federated Unlearning. Yijing Lin, Zhipeng Gao, Hongyang Du, Dusit Niyato, Jiawen Kang, Xiaoyuan Liu |
| 2024 | Individual Welfare Guarantees in the Autobidding World with Machine-learned Advice. Yuan Deng, Negin Golrezaei, Patrick Jaillet, Jason Cheuk Nam Liang, Vahab Mirrokni |
| 2024 | Inductive Cognitive Diagnosis for Fast Student Learning in Web-Based Intelligent Education Systems. Shuo Liu, Junhao Shen, Hong Qian, Aimin Zhou |
| 2024 | Inductive Graph Alignment Prompt: Bridging the Gap between Graph Pre-training and Inductive Fine-tuning From Spectral Perspective. Yuchen Yan, Peiyan Zhang, Zheng Fang, Qingqing Long |
| 2024 | InfoRank: Unbiased Learning-to-Rank via Conditional Mutual Information Minimization. Jiarui Jin, Zexue He, Mengyue Yang, Weinan Zhang, Yong Yu, Jun Wang, Julian J. McAuley |
| 2024 | Infrastructure Ombudsman: Mining Future Failure Concerns from Structural Disaster Response. Md Towhidul Absar Chowdhury, Soumyajit Datta, Naveen Sharma, Ashiqur R. KhudaBukhsh |
| 2024 | Intelligent Model Update Strategy for Sequential Recommendation. Zheqi Lv, Wenqiao Zhang, Zhengyu Chen, Shengyu Zhang, Kun Kuang |
| 2024 | Interface Illusions: Uncovering the Rise of Visual Scams in Cryptocurrency Wallets. Guoyi Ye, Geng Hong, Yuan Zhang, Min Yang |
| 2024 | Interpretable Knowledge Tracing with Multiscale State Representation. Jianwen Sun, Fenghua Yu, Qian Wan, Qing Li, Sannyuya Liu, Xiaoxuan Shen |
| 2024 | Intersectional Two-sided Fairness in Recommendation. Yifan Wang, Peijie Sun, Weizhi Ma, Min Zhang, Yuan Zhang, Peng Jiang, Shaoping Ma |
| 2024 | Invariant Graph Learning for Causal Effect Estimation. Yongduo Sui, Caizhi Tang, Zhixuan Chu, Junfeng Fang, Yuan Gao, Qing Cui, Longfei Li, Jun Zhou, Xiang Wang |
| 2024 | Investigations of Top-Level Domain Name Collisions in Blockchain Naming Services. Daiki Ito, Yuta Takata, Hiroshi Kumagai, Masaki Kamizono |
| 2024 | Is Contrastive Learning Necessary? A Study of Data Augmentation vs Contrastive Learning in Sequential Recommendation. Peilin Zhou, You-Liang Huang, Yueqi Xie, Jingqi Gao, Shoujin Wang, Jae Boum Kim, Sunghun Kim |
| 2024 | Is It Safe to Share Your Files? An Empirical Security Analysis of Google Workspace. Liuhuo Wan, Kailong Wang, Haoyu Wang, Guangdong Bai |
| 2024 | Item-side Fairness of Large Language Model-based Recommendation System. Meng Jiang, Keqin Bao, Jizhi Zhang, Wenjie Wang, Zhengyi Yang, Fuli Feng, Xiangnan He |
| 2024 | Jointly Canonicalizing and Linking Open Knowledge Base via Unified Embedding Learning. Wei Shen, Binhan Yang, Yinan Liu |
| 2024 | KGQuiz: Evaluating the Generalization of Encoded Knowledge in Large Language Models. Yuyang Bai, Shangbin Feng, Vidhisha Balachandran, Zhaoxuan Tan, Shiqi Lou, Tianxing He, Yulia Tsvetkov |
| 2024 | Knowledge-Augmented Large Language Models for Personalized Contextual Query Suggestion. Jinheon Baek, Nirupama Chandrasekaran, Silviu Cucerzan, Allen Herring, Sujay Kumar Jauhar |
| 2024 | LARA: A Light and Anti-overfitting Retraining Approach for Unsupervised Time Series Anomaly Detection. Feiyi Chen, Zhen Qin, MengChu Zhou, Yingying Zhang, Shuiguang Deng, Lunting Fan, Guansong Pang, Qingsong Wen |
| 2024 | LFDe: A Lighter, Faster and More Data-Efficient Pre-training Framework for Event Extraction. Zhigang Kan, Liwen Peng, Yifu Gao, Ning Liu, Linbo Qiao, Dongsheng Li |
| 2024 | Labor Space: A Unifying Representation of the Labor Market via Large Language Models. Seongwoon Kim, Yong-Yeol Ahn, Jaehyuk Park |
| 2024 | Learning Category Trees for ID-Based Recommendation: Exploring the Power of Differentiable Vector Quantization. Qijiong Liu, Jiaren Xiao, Lu Fan, Jieming Zhu, Xiao-Ming Wu |
| 2024 | Learning Scalable Structural Representations for Link Prediction with Bloom Signatures. Tianyi Zhang, Haoteng Yin, Rongzhe Wei, Pan Li, Anshumali Shrivastava |
| 2024 | Learning to Generate Explainable Stock Predictions using Self-Reflective Large Language Models. Kelvin J. L. Koa, Yunshan Ma, Ritchie Ng, Tat-Seng Chua |
| 2024 | Learning to Rewrite Prompts for Personalized Text Generation. Cheng Li, Mingyang Zhang, Qiaozhu Mei, Weize Kong, Michael Bendersky |
| 2024 | Leave No One Behind: Online Self-Supervised Self-Distillation for Sequential Recommendation. Shaowei Wei, Zhengwei Wu, Xin Li, Qintong Wu, Zhiqiang Zhang, Jun Zhou, Lihong Gu, Jinjie Gu |
| 2024 | Linear-Time Graph Neural Networks for Scalable Recommendations. Jiahao Zhang, Rui Xue, Wenqi Fan, Xin Xu, Qing Li, Jian Pei, Xiaorui Liu |
| 2024 | Link Prediction on Multilayer Networks through Learning of Within-Layer and Across-Layer Node-Pair Structural Features and Node Embedding Similarity. Lorenzo Zangari, Domenico Mandaglio, Andrea Tagarelli |
| 2024 | Link Recommendation to Augment Influence Diffusion with Provable Guarantees. Xiaolong Chen, Yifan Song, Jing Tang |
| 2024 | LinkNER: Linking Local Named Entity Recognition Models to Large Language Models using Uncertainty. Zhen Zhang, Yuhua Zhao, Hang Gao, Mengting Hu |
| 2024 | List-aware Reranking-Truncation Joint Model for Search and Retrieval-augmented Generation. Shicheng Xu, Liang Pang, Jun Xu, Huawei Shen, Xueqi Cheng |
| 2024 | Local Centrality Minimization with Quality Guarantees. Atsushi Miyauchi, Lorenzo Severini, Francesco Bonchi |
| 2024 | Long-term Off-Policy Evaluation and Learning. Yuta Saito, Himan Abdollahpouri, Jesse Anderton, Ben Carterette, Mounia Lalmas |
| 2024 | Low Mileage, High Fidelity: Evaluating Hypergraph Expansion Methods by Quantifying the Information Loss. David Y. Kang, Qiaozhu Mei, Sang-Wook Kim |
| 2024 | Lower-Left Partial AUC: An Effective and Efficient Optimization Metric for Recommendation. Wentao Shi, Chenxu Wang, Fuli Feng, Yang Zhang, Wenjie Wang, Junkang Wu, Xiangnan He |
| 2024 | M-scan: A Multi-Scenario Causal-driven Adaptive Network for Recommendation. Jiachen Zhu, Yichao Wang, Jianghao Lin, Jiarui Qin, Ruiming Tang, Weinan Zhang, Yong Yu |
| 2024 | MARIO: Model Agnostic Recipe for Improving OOD Generalization of Graph Contrastive Learning. Yun Zhu, Haizhou Shi, Zhenshuo Zhang, Siliang Tang |
| 2024 | MCFEND: A Multi-source Benchmark Dataset for Chinese Fake News Detection. Yupeng Li, Haorui He, Jin Bai, Dacheng Wen |
| 2024 | MMAdapt: A Knowledge-guided Multi-source Multi-class Domain Adaptive Framework for Early Health Misinformation Detection. Lanyu Shang, Yang Zhang, Bozhang Chen, Ruohan Zong, Zhenrui Yue, Huimin Zeng, Na Wei, Dong Wang |
| 2024 | MMLSCU: A Dataset for Multi-modal Multi-domain Live Streaming Comment Understanding. Zixiang Meng, Qiang Gao, Di Guo, Yunlong Li, Bobo Li, Hao Fei, Shengqiong Wu, Fei Li, Chong Teng, Donghong Ji |
| 2024 | MMPOI: A Multi-Modal Content-Aware Framework for POI Recommendations. Yang Xu, Gao Cong, Lei Zhu, Lizhen Cui |
| 2024 | MSynFD: Multi-hop Syntax Aware Fake News Detection. Liang Xiao, Qi Zhang, Chongyang Shi, Shoujin Wang, Usman Naseem, Liang Hu |
| 2024 | MULAN: Multi-modal Causal Structure Learning and Root Cause Analysis for Microservice Systems. Lecheng Zheng, Zhengzhang Chen, Jingrui He, Haifeng Chen |
| 2024 | Macro Graph Neural Networks for Online Billion-Scale Recommender Systems. Hao Chen, Yuanchen Bei, Qijie Shen, Yue Xu, Sheng Zhou, Wenbing Huang, Feiran Huang, Senzhang Wang, Xiao Huang |
| 2024 | Making Cloud Spot Instance Interruption Events Visible. Kyunghwan Kim, Kyungyong Lee |
| 2024 | Malicious Package Detection using Metadata Information. Sajal Halder, Michael Bewong, Arash Mahboubi, Yinhao Jiang, Md. Rafiqul Islam, Md Zahidul Islam, Ryan H. L. Ip, Muhammad Ejaz Ahmed, Gowri Sankar Ramachandran, Muhammad Ali Babar |
| 2024 | Markovletics: Methods and A Novel Application for Learning Continuous-Time Markov Chain Mixtures. Fabian Spaeh, Charalampos E. Tsourakakis |
| 2024 | Masked Graph Autoencoder with Non-discrete Bandwidths. Ziwen Zhao, Yuhua Li, Yixiong Zou, Jiliang Tang, Ruixuan Li |
| 2024 | MatchNAS: Optimizing Edge AI in Sparse-Label Data Contexts via Automating Deep Neural Network Porting for Mobile Deployment. Hongtao Huang, Xiaojun Chang, Wen Hu, Lina Yao |
| 2024 | Matching Feature Separation Network for Domain Adaptation in Entity Matching. Chenchen Sun, Yang Xu, Derong Shen, Tiezheng Nie |
| 2024 | Mechanism Design for Large Language Models. Paul Dütting, Vahab Mirrokni, Renato Paes Leme, Haifeng Xu, Song Zuo |
| 2024 | Medusa: Unveil Memory Exhaustion DoS Vulnerabilities in Protocol Implementations. Zhengjie Du, Yuekang Li, Yaowen Zheng, Xiaohan Zhang, Cen Zhang, Yi Liu, Sheikh Mahbub Habib, Xinghua Li, Linzhang Wang, Yang Liu, Bing Mao |
| 2024 | Meet Challenges of RTT Jitter, A Hybrid Internet Congestion Control Algorithm. Lianchen Jia, Chao Zhou, Tianchi Huang, Chaoyang Li, Lifeng Sun |
| 2024 | MemeCraft: Contextual and Stance-Driven Multimodal Meme Generation. Han Wang, Roy Ka-Wei Lee |
| 2024 | Memory Disagreement: A Pseudo-Labeling Measure from Training Dynamics for Semi-supervised Graph Learning. Hongbin Pei, Yuheng Xiong, Pinghui Wang, Jing Tao, Jialun Liu, Huiqi Deng, Jie Ma, Xiaohong Guan |
| 2024 | MentaLLaMA: Interpretable Mental Health Analysis on Social Media with Large Language Models. Kailai Yang, Tianlin Zhang, Ziyan Kuang, Qianqian Xie, Jimin Huang, Sophia Ananiadou |
| 2024 | Message Injection Attack on Rumor Detection under the Black-Box Evasion Setting Using Large Language Model. Yifeng Luo, Yupeng Li, Dacheng Wen, Liang Lan |
| 2024 | Metacognitive Retrieval-Augmented Large Language Models. Yujia Zhou, Zheng Liu, Jiajie Jin, Jian-Yun Nie, Zhicheng Dou |
| 2024 | MileCut: A Multi-view Truncation Framework for Legal Case Retrieval. Fuda Ye, Shuangyin Li |
| 2024 | Mining Exploratory Queries for Conversational Search. Wenhan Liu, Ziliang Zhao, Yutao Zhu, Zhicheng Dou |
| 2024 | Mirror Gradient: Towards Robust Multimodal Recommender Systems via Exploring Flat Local Minima. Shanshan Zhong, Zhongzhan Huang, Daifeng Li, Wushao Wen, Jinghui Qin, Liang Lin |
| 2024 | Mitigating Exploitation Bias in Learning to Rank with an Uncertainty-aware Empirical Bayes Approach. Tao Yang, Cuize Han, Chen Luo, Parth Gupta, Jeff M. Phillips, Qingyao Ai |
| 2024 | ModelGo: A Practical Tool for Machine Learning License Analysis. Moming Duan, Qinbin Li, Bingsheng He |
| 2024 | Modeling Balanced Explicit and Implicit Relations with Contrastive Learning for Knowledge Concept Recommendation in MOOCs. Hengnian Gu, Zhiyi Duan, Pan Xie, Dongdai Zhou |
| 2024 | Modeling the Impact of Timeline Algorithms on Opinion Dynamics Using Low-rank Updates. Tianyi Zhou, Stefan Neumann, Kiran Garimella, Aristides Gionis |
| 2024 | Modularized Networks for Few-shot Hateful Meme Detection. Rui Cao, Roy Ka-Wei Lee, Jing Jiang |
| 2024 | More Than Routing: Joint GPS and Route Modeling for Refine Trajectory Representation Learning. Zhipeng Ma, Zheyan Tu, Xinhai Chen, Yan Zhang, Deguo Xia, Guyue Zhou, Yilun Chen, Yu Zheng, Jiangtao Gong |
| 2024 | MuGSI: Distilling GNNs with Multi-Granularity Structural Information for Graph Classification. Tianjun Yao, Jiaqi Sun, Defu Cao, Kun Zhang, Guangyi Chen |
| 2024 | Multi-Label Zero-Shot Product Attribute-Value Extraction. Jiaying Gong, Hoda Eldardiry |
| 2024 | Multi-Scenario Pricing for Hotel Revenue Management. Wendong Xiao, Shuqi Zhang, Zhiyi Huang, Yao Yu |
| 2024 | MultiGPrompt for Multi-Task Pre-Training and Prompting on Graphs. Xingtong Yu, Chang Zhou, Yuan Fang, Xinming Zhang |
| 2024 | Multimodal Query Suggestion with Multi-Agent Reinforcement Learning from Human Feedback. Zheng Wang, Bingzheng Gan, Wei Shi |
| 2024 | Multimodal Relation Extraction via a Mixture of Hierarchical Visual Context Learners. Xiyang Liu, Chunming Hu, Richong Zhang, Kai Sun, Samuel Mensah, Yongyi Mao |
| 2024 | NAT4AT: Using Non-Autoregressive Translation Makes Autoregressive Translation Faster and Better. Huanran Zheng, Wei Zhu, Xiaoling Wang |
| 2024 | NCTM: A Novel Coded Transmission Mechanism for Short Video Deliveries. Zhenge Xu, Qing Li, Wanxin Shi, Yong Jiang, Zhenhui Yuan, Peng Zhang, Gabriel-Miro Muntean |
| 2024 | NETEVOLVE: Social Network Forecasting using Multi-Agent Reinforcement Learning with Interpretable Features. Kentaro Miyake, Hiroyoshi Ito, Christos Faloutsos, Hirotomo Matsumoto, Atsuyuki Morishima |
| 2024 | NPCS: Native Provenance Computation for SPARQL. Zubaria Asma, Daniel Hernández, Luis Galárraga, Giorgos Flouris, Irini Fundulaki, Katja Hose |
| 2024 | Navigating Multidimensional Ideologies with Reddit's Political Compass: Economic Conflict and Social Affinity. Ernesto Colacrai, Federico Cinus, Gianmarco De Francisci Morales, Michele Starnini |
| 2024 | Navigating the Post-API Dilemma. Amrit Poudel, Tim Weninger |
| 2024 | Negative Sampling in Next-POI Recommendations: Observation, Approach, and Evaluation. Hong-Kyun Bae, Yebeen Kim, Hyunjoon Kim, Sang-Wook Kim |
| 2024 | Non-uniform Bid-scaling and Equilibria for Different Auctions: An Empirical Study. Yuan Deng, Jieming Mao, Vahab Mirrokni, Yifeng Teng, Song Zuo |
| 2024 | Not All Asians are the Same: A Disaggregated Approach to Identifying Anti-Asian Racism in Social Media. Fan Wu, Sanyam Lakhanpal, Qian Li, Kookjin Lee, Doowon Kim, Heewon Chae, Kyounghee Hazel Kwon |
| 2024 | Not All Embeddings are Created Equal: Towards Robust Cross-domain Recommendation via Contrastive Learning. Wenhao Yang, Yingchun Jian, Yibo Wang, Shiyin Lu, Lei Shen, Bing Wang, Haihong Tang, Lijun Zhang |
| 2024 | OODREB: Benchmarking State-of-the-Art Methods for Out-Of-Distribution Generalization on Relation Extraction. Haotian Chen, Houjing Guo, Bingsheng Chen, Xiangdong Zhou |
| 2024 | Off-Policy Evaluation for Large Action Spaces via Policy Convolution. Noveen Sachdeva, Lequn Wang, Dawen Liang, Nathan Kallus, Julian J. McAuley |
| 2024 | Off-Policy Evaluation of Slate Bandit Policies via Optimizing Abstraction. Haruka Kiyohara, Masahiro Nomura, Yuta Saito |
| 2024 | On Truthful Item-Acquiring Mechanisms for Reward Maximization. Liang Shan, Shuo Zhang, Jie Zhang, Zihe Wang |
| 2024 | On the Feasibility of Simple Transformer for Dynamic Graph Modeling. Yuxia Wu, Yuan Fang, Lizi Liao |
| 2024 | Online Sequential Decision-Making with Unknown Delays. Ping Wu, Heyan Huang, Zhengyang Liu |
| 2024 | Optimal Engagement-Diversity Tradeoffs in Social Media. Fabian Baumann, Daniel Halpern, Ariel D. Procaccia, Iyad Rahwan, Itai Shapira, Manuel Wüthrich |
| 2024 | Optimizing Network Resilience via Vertex Anchoring. Siyi Teng, Jiadong Xie, Fan Zhang, Can Lu, Juntao Fang, Kai Wang |
| 2024 | Optimizing Polynomial Graph Filters: A Novel Adaptive Krylov Subspace Approach. Keke Huang, Wencai Cao, Hoang Ta, Xiaokui Xiao, Pietro Liò |
| 2024 | PAGE: Equilibrate Personalization and Generalization in Federated Learning. Qian Chen, Zilong Wang, Jiaqi Hu, Haonan Yan, Jianying Zhou, Xiaodong Lin |
| 2024 | PASS: Predictive Auto-Scaling System for Large-scale Enterprise Web Applications. Yunda Guo, Jiake Ge, Panfeng Guo, Yunpeng Chai, Tao Li, Mengnan Shi, Yang Tu, Jian Ouyang |
| 2024 | PMG : Personalized Multimodal Generation with Large Language Models. Xiaoteng Shen, Rui Zhang, Xiaoyan Zhao, Jieming Zhu, Xi Xiao |
| 2024 | POLISH: Adaptive Online Cross-Modal Hashing for Class Incremental Data. Yu-Wei Zhan, Xin Luo, Zhen-Duo Chen, Yongxin Wang, Yinwei Wei, Xin-Shun Xu |
| 2024 | PaCEr: Network Embedding From Positional to Structural. Yuchen Yan, Yongyi Hu, Qinghai Zhou, Lihui Liu, Zhichen Zeng, Yuzhong Chen, Menghai Pan, Huiyuan Chen, Mahashweta Das, Hanghang Tong |
| 2024 | PanoptiChrome: A Modern In-browser Taint Analysis Framework. Rahul Kanyal, Smruti R. Sarangi |
| 2024 | Perceptions in Pixels: Analyzing Perceived Gender and Skin Tone in Real-world Image Search Results. Jeffrey L. Gleason, Avijit Ghosh, Ronald E. Robertson, Christo Wilson |
| 2024 | Perennial Semantic Data Terms of Use for Decentralized Web. Rui Zhao, Jun Zhao |
| 2024 | PhishinWebView: Analysis of Anti-Phishing Entities in Mobile Apps with WebView Targeted Phishing. Yoonjung Choi, Woonghee Lee, Junbeom Hur |
| 2024 | Phishing Vs. Legit: Comparative Analysis of Client-Side Resources of Phishing and Target Brand Websites. Kyungchan Lim, Jaehwan Park, Doowon Kim |
| 2024 | Physical Trajectory Inference Attack and Defense in Decentralized POI Recommendation. Jing Long, Tong Chen, Guanhua Ye, Kai Zheng, Quoc Viet Hung Nguyen, Hongzhi Yin |
| 2024 | Poisoning Attack on Federated Knowledge Graph Embedding. Enyuan Zhou, Song Guo, Zhixiu Ma, Zicong Hong, Tao Guo, Peiran Dong |
| 2024 | Poisoning Federated Recommender Systems with Fake Users. Ming Yin, Yichang Xu, Minghong Fang, Neil Zhenqiang Gong |
| 2024 | Predicting and Presenting Task Difficulty for Crowdsourcing Food Rescue Platforms. Zheyuan Ryan Shi, Jiayin Zhi, Siqi Zeng, Zhicheng Zhang, Ameesh Kapoor, Sean Hudson, Hong Shen, Fei Fang |
| 2024 | Predictive Relevance Uncertainty for Recommendation Systems. Charul Paliwal, Anirban Majumder, Sivaramakrishnan Kaveri |
| 2024 | Prior-Free Mechanism with Welfare Guarantees. Guru Guruganesh, Jon Schneider, Joshua R. Wang |
| 2024 | Privacy-Preserving and Fairness-Aware Federated Learning for Critical Infrastructure Protection and Resilience. Yanjun Zhang, Ruoxi Sun, Liyue Shen, Guangdong Bai, Minhui Xue, Mark Huasong Meng, Xue Li, Ryan K. L. Ko, Surya Nepal |
| 2024 | Proceedings of the ACM on Web Conference 2024, WWW 2024, Singapore, May 13-17, 2024 Tat-Seng Chua, Chong-Wah Ngo, Ravi Kumar, Hady W. Lauw, Roy Ka-Wei Lee |
| 2024 | Prompt-enhanced Federated Content Representation Learning for Cross-domain Recommendation. Lei Guo, Ziang Lu, Junliang Yu, Quoc Viet Hung Nguyen, Hongzhi Yin |
| 2024 | PromptMM: Multi-Modal Knowledge Distillation for Recommendation with Prompt-Tuning. Wei Wei, Jiabin Tang, Lianghao Xia, Yangqin Jiang, Chao Huang |
| 2024 | QUIC is not Quick Enough over Fast Internet. Xumiao Zhang, Shuowei Jin, Yi He, Ahmad Hassan, Z. Morley Mao, Feng Qian, Zhi-Li Zhang |
| 2024 | Query Optimization for Ontology-Mediated Query Answering. Wafaa El Husseini, Cheikh Brahim El Vaigh, François Goasdoué, Hélène Jaudoin |
| 2024 | Query in Your Tongue: Reinforce Large Language Models with Retrievers for Cross-lingual Search Generative Experience. Ping Guo, Yue Hu, Yanan Cao, Yubing Ren, Yunpeng Li, Heyan Huang |
| 2024 | Query2GMM: Learning Representation with Gaussian Mixture Model for Reasoning over Knowledge Graphs. Yuhan Wu, Yuanyuan Xu, Wenjie Zhang, Xiwei Xu, Ying Zhang |
| 2024 | Question Difficulty Consistent Knowledge Tracing. Guimei Liu, Huijing Zhan, Jung-Jae Kim |
| 2024 | ReLLa: Retrieval-enhanced Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation. Jianghao Lin, Rong Shan, Chenxu Zhu, Kounianhua Du, Bo Chen, Shigang Quan, Ruiming Tang, Yong Yu, Weinan Zhang |
| 2024 | RecDCL: Dual Contrastive Learning for Recommendation. Dan Zhang, Yangliao Geng, Wenwen Gong, Zhongang Qi, Zhiyu Chen, Xing Tang, Ying Shan, Yuxiao Dong, Jie Tang |
| 2024 | Recommender Transformers with Behavior Pathways. Zhiyu Yao, Xinyang Chen, Sinan Wang, Qinyan Dai, Yumeng Li, Tanchao Zhu, Mingsheng Long |
| 2024 | Reconciling the Accuracy-Diversity Trade-off in Recommendations. Kenny Peng, Manish Raghavan, Emma Pierson, Jon M. Kleinberg, Nikhil Garg |
| 2024 | RecurScan: Detecting Recurring Vulnerabilities in PHP Web Applications. Youkun Shi, Yuan Zhang, Tianhao Bai, Lei Zhang, Xin Tan, Min Yang |
| 2024 | Reinforcement Learning with Maskable Stock Representation for Portfolio Management in Customizable Stock Pools. Wentao Zhang, Yilei Zhao, Shuo Sun, Jie Ying, Yonggang Xie, Zitao Song, Xinrun Wang, Bo An |
| 2024 | ReliK: A Reliability Measure for Knowledge Graph Embeddings. Maximilian K. Egger, Wenyue Ma, Davide Mottin, Panagiotis Karras, Ilaria Bordino, Francesco Gullo, Aris Anagnostopoulos |
| 2024 | Representation Learning with Large Language Models for Recommendation. Xubin Ren, Wei Wei, Lianghao Xia, Lixin Su, Suqi Cheng, Junfeng Wang, Dawei Yin, Chao Huang |
| 2024 | Retention Depolarization in Recommender System. Xiaoying Zhang, Hongning Wang, Yang Liu |
| 2024 | Rethinking Cross-Domain Sequential Recommendation under Open-World Assumptions. Wujiang Xu, Qitian Wu, Runzhong Wang, Mingming Ha, Qiongxu Ma, Linxun Chen, Bing Han, Junchi Yan |
| 2024 | Rethinking Node-wise Propagation for Large-scale Graph Learning. Xunkai Li, Jingyuan Ma, Zhengyu Wu, Daohan Su, Wentao Zhang, Rong-Hua Li, Guoren Wang |
| 2024 | Revisiting VAE for Unsupervised Time Series Anomaly Detection: A Frequency Perspective. Zexin Wang, Changhua Pei, Minghua Ma, Xin Wang, Zhihan Li, Dan Pei, Saravan Rajmohan, Dongmei Zhang, Qingwei Lin, Haiming Zhang, Jianhui Li, Gaogang Xie |
| 2024 | Revisiting the Behavioral Foundations of User Modeling Algorithms. Jon M. Kleinberg |
| 2024 | RicciNet: Deep Clustering via A Riemannian Generative Model. Li Sun, Jingbin Hu, Suyang Zhou, Zhenhao Huang, Junda Ye, Hao Peng, Zhengtao Yu, Philip S. Yu |
| 2024 | Robust Decision Aggregation with Second-order Information. Yuqi Pan, Zhaohua Chen, Yuqing Kong |
| 2024 | Robust Link Prediction over Noisy Hyper-Relational Knowledge Graphs via Active Learning. Weijian Yu, Jie Yang, Dingqi Yang |
| 2024 | Robust Route Planning under Uncertain Pickup Requests for Last-mile Delivery. Hua Yan, Heng Tan, Haotian Wang, Desheng Zhang, Yu Yang |
| 2024 | RulePrompt: Weakly Supervised Text Classification with Prompting PLMs and Self-Iterative Logical Rules. Miaomiao Li, Jiaqi Zhu, Yang Wang, Yi Yang, Yilin Li, Hongan Wang |
| 2024 | SMUG: Sand Mixing for Unobserved Class Detection in Graph Few-Shot Learning. Chenxu Wang, Xichan Nie, Jinfeng Chen, Pinghui Wang, Junzhou Zhao, Xiaohong Guan |
| 2024 | SPRING: Improving the Throughput of Sharding Blockchain via Deep Reinforcement Learning Based State Placement. Pengze Li, Mingxuan Song, Mingzhe Xing, Zhen Xiao, Qiuyu Ding, Shengjie Guan, Jieyi Long |
| 2024 | SSI, from Specifications to Protocol? Formally Verify Security! Christoph H.-J. Braun, Ross Horne, Tobias Käfer, Sjouke Mauw |
| 2024 | SSTKG: Simple Spatio-Temporal Knowledge Graph for Intepretable and Versatile Dynamic Information Embedding. Ruiyi Yang, Flora D. Salim, Hao Xue |
| 2024 | SatGuard: Concealing Endless and Bursty Packet Losses in LEO Satellite Networks for Delay-Sensitive Web Applications. Jihao Li, Hewu Li, Zeqi Lai, Qian Wu, Yijie Liu, Qi Zhang, Yuanjie Li, Jun Liu |
| 2024 | Scalable Continuous-time Diffusion Framework for Network Inference and Influence Estimation. Keke Huang, Ruize Gao, Bogdan Cautis, Xiaokui Xiao |
| 2024 | Scalable and Effective Generative Information Retrieval. Hansi Zeng, Chen Luo, Bowen Jin, Sheikh Muhammad Sarwar, Tianxin Wei, Hamed Zamani |
| 2024 | Scalable and Provably Fair Exposure Control for Large-Scale Recommender Systems. Riku Togashi, Kenshi Abe, Yuta Saito |
| 2024 | SceneDAPR: A Scene-Level Free-Hand Drawing Dataset for Web-based Psychological Drawing Assessment. Jiwon Kang, Jiwon Kim, Migyeong Yang, Chaehee Park, Taeeun Kim, Hayeon Song, Jinyoung Han |
| 2024 | Search-in-the-Chain: Interactively Enhancing Large Language Models with Search for Knowledge-intensive Tasks. Shicheng Xu, Liang Pang, Huawei Shen, Xueqi Cheng, Tat-Seng Chua |
| 2024 | Self-Guided Robust Graph Structure Refinement. Yeonjun In, Kanghoon Yoon, Kibum Kim, Kijung Shin, Chanyoung Park |
| 2024 | Self-Paced Pairwise Representation Learning for Semi-Supervised Text Classification. Junfan Chen, Richong Zhang, Jiarui Wang, Chunming Hu, Yongyi Mao |
| 2024 | Semantic Evolvement Enhanced Graph Autoencoder for Rumor Detection. Xiang Tao, Liang Wang, Qiang Liu, Shu Wu, Liang Wang |
| 2024 | Social Media Discourses on Interracial Intimacy: Tracking Racism and Sexism through Chinese Geo-located Social Media Data. Zheng Wei, Yixuan Xie, Danyun Xiao, Simin Zhang, Pan Hui, Muzhi Zhou |
| 2024 | Span-Pair Interaction and Tagging for Dialogue-Level Aspect-Based Sentiment Quadruple Analysis. Changzhi Zhou, Zhijing Wu, Dandan Song, Linmei Hu, Yuhang Tian, Jing Xu |
| 2024 | Spectral Heterogeneous Graph Convolutions via Positive Noncommutative Polynomials. Mingguo He, Zhewei Wei, Shikun Feng, Zhengjie Huang, Weibin Li, Yu Sun, Dianhai Yu |
| 2024 | Spot Check Equivalence: An Interpretable Metric for Information Elicitation Mechanisms. Shengwei Xu, Yichi Zhang, Paul Resnick, Grant Schoenebeck |
| 2024 | Stable-Sketch: A Versatile Sketch for Accurate, Fast, Web-Scale Data Stream Processing. Weihe Li, Paul Patras |
| 2024 | Sublinear-Time Opinion Estimation in the Friedkin-Johnsen Model. Stefan Neumann, Yinhao Dong, Pan Peng |
| 2024 | Supervised Fine-Tuning for Unsupervised KPI Anomaly Detection for Mobile Web Systems. Zhaoyang Yu, Shenglin Zhang, Mingze Sun, Yingke Li, Yankai Zhao, Xiaolei Hua, Lin Zhu, Xidao Wen, Dan Pei |
| 2024 | Susceptibility to Unreliable Information Sources: Swift Adoption with Minimal Exposure. Jinyi Ye, Luca Luceri, Julie Jiang, Emilio Ferrara |
| 2024 | SymLearn: A Symbiotic Crowd-AI Collective Learning Framework to Web-based Healthcare Policy Adherence Assessment. Yang Zhang, Ruohan Zong, Lanyu Shang, Huimin Zeng, Zhenrui Yue, Dong Wang |
| 2024 | T Huaiwen Zhang, Xinxin Liu, Qing Yang, Yang Yang, Fan Qi, Shengsheng Qian, Changsheng Xu |
| 2024 | TATKC: A Temporal Graph Neural Network for Fast Approximate Temporal Katz Centrality Ranking. Tianming Zhang, Junkai Fang, Zhengyi Yang, Bin Cao, Jing Fan |
| 2024 | Taxonomy Completion via Implicit Concept Insertion. Jingchuan Shi, Hang Dong, Jiaoyan Chen, Zhe Wu, Ian Horrocks |
| 2024 | Team Formation amidst Conflicts. Iasonas Nikolaou, Evimaria Terzi |
| 2024 | Temporal Conformity-aware Hawkes Graph Network for Recommendations. Chenglong Ma, Yongli Ren, Pablo Castells, Mark Sanderson |
| 2024 | The Double Edged Sword: Identifying Authentication Pages and their Fingerprinting Behavior. Asuman Senol, Alisha Ukani, Dylan Cutler, Igor Bilogrevic |
| 2024 | The Dynamics of (Not) Unfollowing Misinformation Spreaders. Joshua Ashkinaze, Eric Gilbert, Ceren Budak |
| 2024 | The Matter of Captchas: An Analysis of a Brittle Security Feature on the Modern Web. Behzad Ousat, Esteban Schafir, Duc C. Hoang, Mohammad Ali Tofighi, Cuong V. Nguyen, Sajjad Arshad, A. Selcuk Uluagac, Amin Kharraz |
| 2024 | Tight Competitive and Variance Analyses of Matching Policies in Gig Platforms. Pan Xu |
| 2024 | TikTok and the Art of Personalization: Investigating Exploration and Exploitation on Social Media Feeds. Karan Vombatkere, Sepehr Mousavi, Savvas Zannettou, Franziska Roesner, Krishna P. Gummadi |
| 2024 | Top-Personalized-K Recommendation. Wonbin Kweon, SeongKu Kang, Sanghwan Jang, Hwanjo Yu |
| 2024 | Toward Practical Entity Alignment Method Design: Insights from New Highly Heterogeneous Knowledge Graph Datasets. Xuhui Jiang, Chengjin Xu, Yinghan Shen, Yuanzhuo Wang, Fenglong Su, Zhichao Shi, Fei Sun, Zixuan Li, Jian Guo, Huawei Shen |
| 2024 | Towards Cross-Table Masked Pretraining for Web Data Mining. Chao Ye, Guoshan Lu, Haobo Wang, Liyao Li, Sai Wu, Gang Chen, Junbo Zhao |
| 2024 | Towards Deeper Understanding of PPR-based Embedding Approaches: A Topological Perspective. Xingyi Zhang, Zixuan Weng, Sibo Wang |
| 2024 | Towards Efficient Communication and Secure Federated Recommendation System via Low-rank Training. Ngoc-Hieu Nguyen, Tuan-Anh Nguyen, Tuan Nguyen, Vu Tien Hoang, Dung D. Le, Kok-Seng Wong |
| 2024 | Towards Energy-efficient Federated Learning via INT8-based Training on Mobile DSPs. Jinliang Yuan, Shangguang Wang, Hongyu Li, Daliang Xu, Yuanchun Li, Mengwei Xu, Xuanzhe Liu |
| 2024 | Towards Expansive and Adaptive Hard Negative Mining: Graph Contrastive Learning via Subspace Preserving. Zhezheng Hao, Haonan Xin, Long Wei, Liaoyuan Tang, Rong Wang, Feiping Nie |
| 2024 | Towards Explainable Harmful Meme Detection through Multimodal Debate between Large Language Models. Hongzhan Lin, Ziyang Luo, Wei Gao, Jing Ma, Bo Wang, Ruichao Yang |
| 2024 | Towards Personalized Privacy: User-Governed Data Contribution for Federated Recommendation. Liang Qu, Wei Yuan, Ruiqi Zheng, Lizhen Cui, Yuhui Shi, Hongzhi Yin |
| 2024 | Towards the Identifiability and Explainability for Personalized Learner Modeling: An Inductive Paradigm. Jiatong Li, Qi Liu, Fei Wang, Jiayu Liu, Zhenya Huang, Fangzhou Yao, Linbo Zhu, Yu Su |
| 2024 | Trajectory-wise Iterative Reinforcement Learning Framework for Auto-bidding. Haoming Li, Yusen Huo, Shuai Dou, Zhenzhe Zheng, Zhilin Zhang, Chuan Yu, Jian Xu, Fan Wu |
| 2024 | Triage of Messages and Conversations in a Large-Scale Child Victimization Corpus. Prasanna Lakkur Subramanyam, Mohit Iyyer, Brian Neil Levine |
| 2024 | Trident: A Universal Framework for Fine-Grained and Class-Incremental Unknown Traffic Detection. Ziming Zhao, Zhaoxuan Li, Zhuoxue Song, Wenhao Li, Fan Zhang |
| 2024 | Uncovering the Deep Filter Bubble: Narrow Exposure in Short-Video Recommendation. Nicholas Sukiennik, Chen Gao, Nian Li |
| 2024 | Uncovering the Hidden Data Costs of Mobile YouTube Video Ads. Emaan Atique, Saad Sher Alam, Harris Ahmad, Ihsan Ayyub Qazi, Zafar Ayyub Qazi |
| 2024 | Understanding GDPR Non-Compliance in Privacy Policies of Alexa Skills in European Marketplaces. Song Liao, Mohammed Aldeen, Jingwen Yan, Long Cheng, Xiapu Luo, Haipeng Cai, Hongxin Hu |
| 2024 | Understanding Human Preferences: Towards More Personalized Video to Text Generation. Yihan Wu, Ruihua Song, Xu Chen, Hao Jiang, Zhao Cao, Jin Yu |
| 2024 | Unfiltered: Measuring Cloud-based Email Filtering Bypasses. Sumanth Rao, Enze Liu, Grant Ho, Geoffrey M. Voelker, Stefan Savage |
| 2024 | UniLP: Unified Topology-aware Generative Framework for Link Prediction in Knowledge Graph. Ben Liu, Miao Peng, Wenjie Xu, Xu Jia, Min Peng |
| 2024 | UniTime: A Language-Empowered Unified Model for Cross-Domain Time Series Forecasting. Xu Liu, Junfeng Hu, Yuan Li, Shizhe Diao, Yuxuan Liang, Bryan Hooi, Roger Zimmermann |
| 2024 | Unified Uncertainty Estimation for Cognitive Diagnosis Models. Fei Wang, Qi Liu, Enhong Chen, Chuanren Liu, Zhenya Huang, Jinze Wu, Shijin Wang |
| 2024 | UnifiedSSR: A Unified Framework of Sequential Search and Recommendation. Jiayi Xie, Shang Liu, Gao Cong, Zhenzhong Chen |
| 2024 | Unify Graph Learning with Text: Unleashing LLM Potentials for Session Search. Songhao Wu, Quan Tu, Hong Liu, Jia Xu, Zhongyi Liu, Guannan Zhang, Ran Wang, Xiuying Chen, Rui Yan |
| 2024 | Unifying Local and Global Knowledge: Empowering Large Language Models as Political Experts with Knowledge Graphs. Xinyi Mou, Zejun Li, Hanjia Lyu, Jiebo Luo, Zhongyu Wei |
| 2024 | Unity is Strength? Benchmarking the Robustness of Fusion-based 3D Object Detection against Physical Sensor Attack. Zizhi Jin, Xuancun Lu, Bo Yang, Yushi Cheng, Chen Yan, Xiaoyu Ji, Wenyuan Xu |
| 2024 | Unleashing the Power of Knowledge Graph for Recommendation via Invariant Learning. Shuyao Wang, Yongduo Sui, Chao Wang, Hui Xiong |
| 2024 | Unlocking the Non-deterministic Computing Power with Memory-Elastic Multi-Exit Neural Networks. Jiaming Huang, Yi Gao, Wei Dong |
| 2024 | Unmasking the Web of Deceit: Uncovering Coordinated Activity to Expose Information Operations on Twitter. Luca Luceri, Valeria Pantè, Keith Burghardt, Emilio Ferrara |
| 2024 | Unraveling the Dynamics of Stable and Curious Audiences in Web Systems. Rodrigo Alves, Antoine Ledent, Renato Assunção, Pedro O. S. Vaz de Melo, Marius Kloft |
| 2024 | Unveiling Climate Drivers via Feature Importance Shift Analysis in New Zealand. Bowen Chen, Gillian Dobbie, Neelesh Rampal, Yun Sing Koh |
| 2024 | Unveiling Delay Effects in Traffic Forecasting: A Perspective from Spatial-Temporal Delay Differential Equations. Qingqing Long, Zheng Fang, Chen Fang, Chong Chen, Pengfei Wang, Yuanchun Zhou |
| 2024 | Unveiling the Invisible: Detection and Evaluation of Prototype Pollution Gadgets with Dynamic Taint Analysis. Mikhail Shcherbakov, Paul Moosbrugger, Musard Balliu |
| 2024 | Unveiling the Paradox of NFT Prosperity. Jintao Huang, Pengcheng Xia, Jiefeng Li, Kai Ma, Gareth Tyson, Xiapu Luo, Lei Wu, Yajin Zhou, Wei Cai, Haoyu Wang |
| 2024 | Uplift Modeling for Target User Attacks on Recommender Systems. Wenjie Wang, Changsheng Wang, Fuli Feng, Wentao Shi, Daizong Ding, Tat-Seng Chua |
| 2024 | UrbanCLIP: Learning Text-enhanced Urban Region Profiling with Contrastive Language-Image Pretraining from the Web. Yibo Yan, Haomin Wen, Siru Zhong, Wei Chen, Haodong Chen, Qingsong Wen, Roger Zimmermann, Yuxuan Liang |
| 2024 | User Distribution Mapping Modelling with Collaborative Filtering for Cross Domain Recommendation. Weiming Liu, Chaochao Chen, Xinting Liao, Mengling Hu, Jiajie Su, Yanchao Tan, Fan Wang |
| 2024 | User Response in Ad Auctions: An MDP Formulation of Long-term Revenue Optimization. Yang Cai, Zhe Feng, Christopher Liaw, Aranyak Mehta, Grigoris Velegkas |
| 2024 | Using Model Calibration to Evaluate Link Prediction in Knowledge Graphs. Aishwarya Rao, Narayanan Asuri Krishnan, Carlos R. Rivero |
| 2024 | VilLain: Self-Supervised Learning on Homogeneous Hypergraphs without Features via Virtual Label Propagation. Geon Lee, Soo Yong Lee, Kijung Shin |
| 2024 | WEFix: Intelligent Automatic Generation of Explicit Waits for Efficient Web End-to-End Flaky Tests. Xinyue Liu, Zihe Song, Weike Fang, Wei Yang, Weihang Wang |
| 2024 | Weakly Supervised Anomaly Detection via Knowledge-Data Alignment. Haihong Zhao, Chenyi Zi, Yang Liu, Chen Zhang, Yan Zhou, Jia Li |
| 2024 | What News Do People Get on Social Media? Analyzing Exposure and Consumption of News through Data Donations. Salim Chouaki, Abhijnan Chakraborty, Oana Goga, Savvas Zannettou |
| 2024 | When Federated Recommendation Meets Cold-Start Problem: Separating Item Attributes and User Interactions. Chunxu Zhang, Guodong Long, Tianyi Zhou, Zijian Zhang, Peng Yan, Bo Yang |
| 2024 | When Imbalance Meets Imbalance: Structure-driven Learning for Imbalanced Graph Classification. Wei Xu, Pengkun Wang, Zhe Zhao, Binwu Wang, Xu Wang, Yang Wang |
| 2024 | Which LLM to Play? Convergence-Aware Online Model Selection with Time-Increasing Bandits. Yu Xia, Fang Kong, Tong Yu, Liya Guo, Ryan A. Rossi, Sungchul Kim, Shuai Li |
| 2024 | Whole Page Unbiased Learning to Rank. Haitao Mao, Lixin Zou, Yujia Zheng, Jiliang Tang, Xiaokai Chu, Jiashu Zhao, Qian Wang, Dawei Yin |
| 2024 | Zero-shot Image Classification with Logic Adapter and Rule Prompt. Dongran Yu, Xueyan Liu, Bo Yang |
| 2024 | ZipZap: Efficient Training of Language Models for Large-Scale Fraud Detection on Blockchain. Sihao Hu, Tiansheng Huang, Ka-Ho Chow, Wenqi Wei, Yanzhao Wu, Ling Liu |
| 2024 | λGrapher: A Resource-Efficient Serverless System for GNN Serving through Graph Sharing. Haichuan Hu, Fangming Liu, Qiangyu Pei, Yongjie Yuan, Zichen Xu, Lin Wang |