KDD

Exploring Big Five Personality and AI Capability Effects in LLM-Simulated Negotiation Dialogues

Myke C. Cohen, Zhe Su, Hsien-Te Kao, Daniel Nguyen, Spencer Lynch, Maarten Sap, Svitlana Volkova

机构 * Aptima, Inc.（Aptima公司） ； Human Systems Engineering, Arizona State University（亚利桑那州立大学人类系统工程系） ； Language Technologies Institute, Carnegie Mellon University（卡内基梅隆大学语言技术研究所） 纠错

Comments Presented at the KDD 2025 Workshop on Evaluation and Trustworthiness of Agentic and Generative AI Models under the title "Evaluating the LLM-simulated Impacts of Big Five Personality Traits and AI Capabilities on Social Negotiations" (https://kdd-eval-workshop.github.io/genai-evaluation-kdd2025/assets/papers/Submission%2036.pdf)

Addressing Graph Anomaly Detection via Causal Edge Separation and Spectrum

Zengyi Wo, Wenjun Wang, Minglai Shao, Chang Liu, Yumeng Wang, Yueheng Sun

机构 * Tianjin University（天津大学） 纠错

Comments Proceedings of the 2024 KDD Workshop

Improving Fairness in Graph Neural Networks via Counterfactual Debiasing

Zengyi Wo, Chang Liu, Yumeng Wang, Minglai Shao, Wenjun Wang

机构 * Tianjin University（天津大学） 纠错

Comments Proceedings of the 2024 KDD Workshop

SSD-TS: Exploring the Potential of Linear State Space Models for Diffusion Models in Time Series Imputation

Hongfan Gao, Wangmeng Shen, Xiangfei Qiu, Ronghui Xu, Jilin Hu, Bin Yang

机构 * East China Normal University（东华师范大学） 纠错

Comments KDD' 25

Benchmark Dataset Generation and Evaluation for Excel Formula Repair with LLMs

Ananya Singha, Harshita Sahijwani, Walt Williams, Emmanuel Aboah Boateng, Nick Hausman, Miguel Di Luca, Keegan Choudhury, Chaya Binet, Vu Le, Tianwei Chen, Oryan Rokeah Chen, Sulaiman Vesal, Sadid Hasan

机构 * Microsoft（微软） 纠错

Comments Accepted at the KDD workshop on Evaluation and Trustworthiness of Agentic and Generative AI Models

SAGE: Scale-Aware Gradual Evolution for Continual Knowledge Graph Embedding

Yifei Li, Lingling Zhang, Hang Yan, Tianzhe Zhao, Zihan Ma, Muye Huang, Jun Liu

机构 * Xi'an Jiaotong University（西安交通大学） 纠错

Comments 10 pages, 5 figures, Accepted at KDD 2025, code available at https://github.com/lyfxjtu/Dynamic-Embedding

Compressive Meta-Learning

Daniel Mas Montserrat, David Bonet, Maria Perera, Xavier Giró-i-Nieto, Alexander G. Ioannidis

机构 * Stanford University（斯坦福大学） ； University of California, Santa Cruz（加州大学圣克鲁兹分校） ； Polytechnic University of Catalonia（加泰罗尼亚理工大学） 纠错

Comments Extended version of a paper accepted at KDD '25

Journal ref Proc. 31st ACM SIGKDD Conf. on Knowledge Discovery and Data Mining, 2, 2102-2113 (2025)

Measuring Time Series Forecast Stability for Demand Planning

Steven Klee, Yuntian Xia

机构 * Amazon Web Services（亚马逊网络服务） 纠错

Comments 6 pages, 3 figures; KDD '25

A New Query Expansion Approach via Agent-Mediated Dialogic Inquiry

Wonduk Seo, Hyunjin An, Seunghyun Lee

机构 * Enhans Seoul, South Korea（首尔增强韩国） 纠错

Comments Accepted by ACM SIGKDD 2025 Workshop on AI Agent for Information Retrieval (Agent4IR)

Mini-Game Lifetime Value Prediction in WeChat

Aochuan Chen, Yifan Niu, Ziqi Gao, Yujie Sun, Shoujun Liu, Gong Chen, Yang Liu, Jia Li

机构 * The Hong Kong University of Science and Technology (Guangzhou)（香港科学与技术大学（广州）） ； Tencent Inc.（腾讯公司） 纠错

Comments KDD ADS Track 2025

Scaling Transformers for Discriminative Recommendation via Generative Pretraining

Chunqi Wang, Bingchao Wu, Zheng Chen, Lei Shen, Bing Wang, Xiaoyi Zeng

Comments KDD'25

UoMo: A Universal Model of Mobile Traffic Forecasting for Wireless Network Optimization

Haoye Chai, Shiyuan Zhang, Xiaoqian Qi, Baohua Qiu, Yong Li

机构 * Department of Electronic Engineering, BNRist, Tsinghua University（电子工程系，BNRist，清华大学） 纠错

Comments 2025 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2025

CAMEF: Causal-Augmented Multi-Modality Event-Driven Financial Forecasting by Integrating Time Series Patterns and Salient Macroeconomic Announcements

Yang Zhang, Wenbo Yang, Jun Wang, Qiang Ma, Jie Xiong

机构 * Southwestern University of Finance and Economics（西南财经大学） ； Kyoto Institute of Technology（京都技术大学） 纠错

Comments Accepted in SIGKDD 2025

Breaking the Top-$K$ Barrier: Advancing Top-$K$ Ranking Metrics Optimization in Recommender Systems

Weiqin Yang, Jiawei Chen, Shengjia Zhang, Peng Wu, Yuegang Sun, Yan Feng, Chun Chen, Can Wang

机构 * Zhejiang University（浙江大学） ； Beijing Technology and Business University（北京科技与商业大学） 纠错

Comments Accepted by KDD 2025

Journal ref Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2 (2025) 3542 - 3552

Zero-Shot Retrieval for Scalable Visual Search in a Two-Sided Marketplace

Andre Rusli, Shoma Ishimoto, Sho Akiyama, Aman Kumar Singh

机构 * Mercari, Inc.（Mercari公司） 纠错

Comments 6 pages, KDD 2025 Workshop on Two-sided Marketplace Optimization: Search, Pricing, Matching & Growth (TSMO)

GuARD: Effective Anomaly Detection through a Text-Rich and Graph-Informed Language Model

Yunhe Pang, Bo Chen, Fanjin Zhang, Yanghui Rao, Evgeny Kharlamov, Jie Tang

机构 * School of Computer Science and Engineering（计算机科学与工程学院） ； Sun Yat-Sen University（中山大学） ； Department of Computer Science and Technology（计算机科学与技术系） ； Tsinghua University（清华大学） ； Robert Bosch GmbH（博世集团） 纠错

Comments Accepted at KDD 2025

A Scalable Pretraining Framework for Link Prediction with Efficient Adaptation

Yu Song, Zhigang Hua, Harry Shomer, Yan Xie, Jingzhe Liu, Bo Long, Hui Liu

机构 * Computer Science and Engineering（计算机科学与工程） ； Michigan State University（密歇根州立大学） ； Meta 纠错

Comments Accepted by KDD 2025 Research Track

How Well Do LLMs Represent Values Across Cultures? Empirical Analysis of LLM Responses Based on Hofstede Cultural Dimensions

Julia Kharchenko, Tanya Roosta, Aman Chadha, Chirag Shah

机构 * University of Washington（华盛顿大学） ； UC Berkeley, Amazon（伯克利大学、亚马逊） ； Stanford University, Amazon GenAI（斯坦福大学、亚马逊生成人工智能） 纠错

Comments KDD 2025

Personalized Recommendation of Dish and Restaurant Collections on iFood

Fernando F. Granado, Davi A. Bezerra, Iuri Queiroz, Nathan Oliveira, Pedro Fernandes, Bruno Schock

机构 * iFood 纠错

Comments Workshop on Two-sided Marketplace Optimization: Search, Discovery, Matching, Pricing & Growth in conjunction with KDD Conference (KDD 2025) in Toronto, Canada

LaTCoder: Converting Webpage Design to Code with Layout-as-Thought

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

Comments KDD 2025 v2

VFLAIR-LLM: A Comprehensive Framework and Benchmark for Split Learning of LLMs

Zixuan Gu, Qiufeng Fan, Long Sun, Yang Liu, Xiaojun Ye

Comments 12 pages, 10 figures, published in KDD2025

Journal ref In Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2 (KDD'25), August 3-7, 2025, Toronto, ON, Canada. ACM, New York, NY, USA, 12 pages

A Survey of WebAgents: Towards Next-Generation AI Agents for Web Automation with Large Foundation Models

Liangbo Ning, Ziran Liang, Zhuohang Jiang, Haohao Qu, Yujuan Ding, Wenqi Fan, Xiao-yong Wei, Shanru Lin, Hui Liu, Philip S. Yu, Qing Li

机构 * The Hong Kong Polytechnic University（香港理工大学） ； City University of Hong Kong（香港城市大学） ； Michigan State University（密歇根州立大学） ； University of Illinois at Chicago（伊利诺伊大学芝加哥分校） 纠错

Comments This is the long version of the corresponding survey paper accepted by KDD 2025. The tutorial and corresponding slides are available at https://biglemon-ning.github.io/WebAgents/

CCSBench: Evaluating Compositional Controllability in LLMs for Scientific Document Summarization

Yixi Ding, Jiaying Wu, Tongyao Zhu, Yanxia Qin, Qian Liu, Min-Yen Kan

机构 * National University of Singapore（新加坡国立大学） ； Singapore University of Technology and Design（新加坡科技设计大学） ； Sea AI Lab（Sea AI实验室） 纠错

Comments Accepted to KDD 2025 SciSoc LLM Workshop: Large Language Models for Scientific and Societal Advances

Counterfactual Reciprocal Recommender Systems for User-to-User Matching

Kazuki Kawamura, Takuma Udagawa, Kei Tateno

机构 * Sony Group Corporation（索尼集团） 纠错

Comments 9 pages, 2 figures. Accepted for publication at the Workshop on Two-sided Marketplace Optimization (TSMO '25), held in conjunction with the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2025), Toronto, Canada

Neural Predictive Control to Coordinate Discrete- and Continuous-Time Models for Time-Series Analysis with Control-Theoretical Improvements

Haoran Li, Muhao Guo, Yang Weng, Hanghang Tong

机构 * Arizona State University（亚利桑那州立大学） ； University of Illinois at Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校） 纠错

Comments 14 pages, submitted to ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Mitigating Persistent Client Dropout in Asynchronous Decentralized Federated Learning

Ignacy Stępka, Nicholas Gisolfi, Kacper Trębacz, Artur Dubrawski

机构 * Carnegie Mellon University（卡内基梅隆大学） 纠错

Comments Presented on FedKDD Workshop at KDD 2025

End-to-End Personalization: Unifying Recommender Systems with Large Language Models

Danial Ebrat, Tina Aminian, Sepideh Ahmadian, Luis Rueda

机构 * University of Windsor（温莎大学） 纠错

Comments Second Workshop on Generative AI for Recommender Systems and Personalization at the ACM Conference on Knowledge Discovery and Data Mining (GenAIRecP@KDD 2025)

Oldie but Goodie: Re-illuminating Label Propagation on Graphs with Partially Observed Features

Sukwon Yun, Xin Liu, Yunhak Oh, Junseok Lee, Tianlong Chen, Tsuyoshi Murata, Chanyoung Park

机构 * The University of North Carolina at Chapel Hill（北卡罗来纳大学教堂山分校） ； National Institute of Advanced Industrial Science（国家先进工业科学研究院） ； Institute of Science Tokyo（东京科学研究院） 纠错

Comments KDD 2025

Explaining GNN Explanations with Edge Gradients

Jesse He, Akbar Rafiey, Gal Mishne, Yusu Wang

机构 * Halıcıoğlu Data Science Institute（哈尔奇奥格卢数据科学研究所） ； Universiy of California, San Diego（加州大学圣地亚哥分校） ； Computer Science and Engineering（计算机科学与工程） ； New York University（纽约大学） 纠错

Comments KDD 2025

Journal ref KDD '25: Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2 (2025) Pages 884 - 895

FECT: Factuality Evaluation of Interpretive AI-Generated Claims in Contact Center Conversation Transcripts

Hagyeong Shin, Binoy Robin Dalal, Iwona Bialynicka-Birula, Navjot Matharu, Ryan Muir, Xingwei Yang, Samuel W. K. Wong

机构 * Cresta, University of Waterloo（Cresta，滑铁卢大学） 纠错

Comments Accepted for an oral presentation at Agentic & GenAI Evaluation KDD 2025: KDD workshop on Evaluation and Trustworthiness of Agentic and Generative AI Models