Tail-Aware Data Augmentation for Long-Tail Sequential Recommendation
关注尾部的数据增强用于长尾序列推荐
AI总结 TADA通过增强尾部物品交互频率并保持头部性能,提升长尾序列推荐模型的学习能力。
Comments Accepted by WWW 2026
期刊&会议
The Web Conference · 会议 · Web
关注尾部的数据增强用于长尾序列推荐
AI总结 TADA通过增强尾部物品交互频率并保持头部性能,提升长尾序列推荐模型的学习能力。
Comments Accepted by WWW 2026
我们需要一个更稳健的分类器:双因果学习赋能领域增量时间序列分类
机构 * School of Software, Northeastern University(东北大学软件学院) ; Institute of Artificial Intelligence and Robotics, Xi'an Jiaotong University(西安交通大学人工智能与机器人研究所) ; College of Computer Science and Technology, National University of Defense Technology(国防科技大学计算机科学与技术学院) ; School of Software, University of Science and Technology of China(中国科学技术大学软件学院)
AI总结 本文提出双因果学习框架DualCD,通过解耦因果特征与虚假特征,提升领域增量时间序列分类的鲁棒性。
Comments This paper has been accepted for publication at ACM WWW 2026
STCRank: 时空协同排序用于快手电商互动推荐系统
AI总结 STCRank通过时空协同排序解决快手电商互动推荐系统中多目标协作与多槽协作问题,提升推荐效果与用户参与度。
Comments Accepted as an oral paper by WWW26 Human-centered recommender systems (HCRS) workshop (https://hcrec.github.io/)
COINS: 语义ID增强的冷启动物品表示法用于电商搜索点击率预测
机构 * Kuaishou Inc.(快手公司)
AI总结 COINS通过融合语义ID的协同信息与内容信息,提升冷启动物品的点击率预测精度,实现电商搜索的多样性与推荐效果的双重提升。
Comments Accepted by WWW26
何时触发:通过毒性评估提升LLM公平性
机构 * RMIT University(拉筹纳斯大学) ; Jilin University(吉林大学) ; Dalian University of Technology(大连理工大学)
AI总结 FairToT通过推理时的提示引导毒性评估,提升LLM在不同群体间的公平性,减少群体差异并保持预测稳定性。
Comments Accepted by Findings of WWW 2026
理解VTuber转世的后果
AI总结 研究分析VTuber转世现象对职业和行业的影响,揭示其对Nakanohito、公司及观众的负面影响,并提出可持续发展的建议。
Comments Accepted to The ACM Web Conference 2026 (WWW '26), Web4Good Track
Grad: 图神经网络在图欺诈检测中的引导关系扩散生成用于图增强
机构 * Tongji University Shanghai China ; The University of New South Wales Sydney Australia ; Tongji University \& Shanghai Artificial Intelligence Laboratory Shanghai China ; Wechat Pay, Tencent Inc. Shenzhen China ; Tongji University ; The University of New South Wales ; Tongji University \& Shanghai Artificial Intelligence Laboratory ; Wechat Pay, Tencent Inc.
AI总结 Grad通过引导关系扩散生成和监督图对比学习,提升图欺诈检测中欺诈与良性用户差异,有效识别隐藏欺诈信号。
Comments Accepted by The Web Conference 2025 (WWW'25). 12 pages, includes implementation details. Code: https://github.com/AI4Risk/antifraud and https://github.com/Muyiiiiii/WWW25-Grad
Journal ref Proceedings of the ACM Web Conference 2025 (WWW '25), April 28-May 2, 2025, Sydney, NSW, Australia
更少的代价:Pinterest冷启动推荐的高效策略
机构 * Pinterest
AI总结 Pinterest提出了一种高效策略,通过轻量级模型、残差连接、分数正则化和流形混合技术,提升冷启动推荐效果,使新鲜内容参与度提升10%。
Comments Submitted to the WWW'26
利用异质溢出效应以最大化上下文老虎机奖励
机构 * University of Illinois Chicago(伊利诺伊大学芝加哥分校)
AI总结 本文提出一种考虑异质溢出效应的上下文老虎机框架,通过引入邻居行为和网络结构信息提升推荐奖励。
Journal ref Proceedings of the ACM Web Conference 2025 (WWW 25), April 28- May 2, 2025, Sydney, Australia, pp. 3049-3060
机构 * Seoul National University(首尔国立大学) ; Osaka University(大阪大学) ; Yonsei University(延世大学)
Comments Under review at The Web Conference 2026 (Semantics & Knowledge track). Code will be released upon acceptance. This arXiv v1 contains no repository links to preserve double-blind review
机构 * CCS\&CS, DISSec, Nankai University(计算机科学与技术系、信息安全与保密系、南开大学) ; University of Louisville(路易斯维尔大学) ; University of North Texas(北德克萨斯大学)
Comments Accepted by The Web Conference 2025
机构 * University of Alberta Edmonton, AB Canada ; Netflix, Inc. Los Gatos, CA USA ; Netflix, Inc. \& Cornell University New York, NY USA ; University of Alberta ; Netflix, Inc. ; Netflix, Inc. \& Cornell University
Comments In the proceedings of the Web Conference (WWW) 2025 (11 pages)
机构 * Tongji University Shanghai China ; University of Technology Sydney Sydney NSW Australia ; Tongji University \& Shanghai Artificial Intelligence Laboratory Shanghai China ; China Futures Market Monitoring Center Beijing China ; Tongji University ; University of Technology Sydney ; Tongji University \& Shanghai Artificial Intelligence Laboratory ; China Futures Market Monitoring Center
Comments 10 pages, 5 figures, ACM the web conference 2025
Comments Published in ACM WWW 2025
Comments Accepted at WWW 25 Industrial Track
机构 * Southwestern University of Finance and Economics(西南财经大学) ; University of Electronic Science and Technology of China(电子科技大学)
Comments WWW 2025
机构 * Center on Frontiers of Computing Studies, Peking University(前沿计算研究中心,北京大学) ; Department of Electrical Engineering and Computer Sciences, University of California, Berkeley(电气工程与计算机科学系,加州大学伯克利分校) ; School of Engineering and Applied Sciences, Harvard University(工程与应用科学系,哈佛大学) ; Department of Computer Science, Yale University(计算机科学系,耶鲁大学)
Comments A preliminary version was published at the Web Conference (WWW) 2022. This version updates references and figures
Comments Accepted by The Web Conference 2025 (WWW2025)
机构 * Alibaba Group(阿里巴巴集团)
Comments WWW '25: Companion Proceedings of the ACM on Web Conference 2025 Pages 919 - 923 https://doi.org/10.1145/3701716.3715541
Journal ref WWW '25: Companion Proceedings of the ACM on Web Conference 2025
机构 * AI at Meta(Meta人工智能)
Comments Accepted by the ACM Web Conference (WWW) 2025 Industrial Track as Oral Presentation
Comments Accepted by WWW2025
机构 * College of Intelligence and Computing(智能与计算学院) ; Tianjin University(天津大学) ; Northwestern Polytechnical University(西北工业大学)
Comments Accepted by WWW 2025
Journal ref Proceedings of the ACM on Web Conference 2025, 1129-1141
机构 * Zhejiang University(浙江大学) ; National University of Singapore(新加坡国立大学) ; Alibaba Group(阿里巴巴集团)
Comments Accepted by International World Wide Web Conference (WWW) 2025
Comments WWW '25: Proceedings of the ACM on Web Conference 2025
机构 * School of AI, Beihang University(北京航空航天大学人工智能学院) ; Beijing Advanced Innovation Center(北京先进创新中心)
Comments WWW2025 WSAI BESTPAPER
Comments Accepted at WWW '25
机构 * University of California San Diego(加州大学圣地亚哥分校) ; ZOZO Research(ZOZO研究) ; Waseda University(早稻田大学) ; University of Southern California(南加州大学) ; Chiba Institute of Technology(千叶科学技术大学) ; The Hong Kong University of Science and Technology(香港科技大学)
Comments This manuscript has been accepted for presentation at The Web Conference (WWW) 2025
机构 * Rutgers University(罗格斯大学) ; University of Technology Sydney(悉尼技术大学) ; University of Illinois Urbana-Champaign(伊利诺伊大学厄巴纳-香槟分校) ; Nanyang Technological University(南洋理工大学)
Comments Findings of ACL 2025 and WWW2025@HCRS
机构 * Institute of Information Engineering, Chinese Academy of Sciences(信息工程研究所,中国科学院) ; School of Cyber Security, UCAS(网络安全学院,UCAS) ; Tongyi Lab, Alibaba Group(通义实验室,阿里巴巴集团) ; Academy of Mathematics and Systems Science, Chinese Academy of Sciences(数学系统科学学院,中国科学院)
Comments 15 pages, 8 figures, published to WWW 2025
Journal ref The ACM Web Conference 2025
Journal ref WWW '25: Companion Proceedings of the ACM on Web Conference 2025