KDD

MetaOOD: Automatic Selection of OOD Detection Models

Yuehan Qin, Yichi Zhang, Yi Nian, Xueying Ding, Yue Zhao

Comments Best paper at 2024 KDD Workshop on Resource-Efficient Learning. Extended version at ICLR 2025

Applying Deep Learning to Ads Conversion Prediction in Last Mile Delivery Marketplace

Di Li, Xiaochang Miao, Huiyu Song, Chao Chu, Hao Xu, Mandar Rahurkar

Comments 10 pages, 5 figures, submitted to KDD

Non-Homophilic Graph Pre-Training and Prompt Learning

Xingtong Yu, Jie Zhang, Yuan Fang, Renhe Jiang

Comments Accepted by KDD 2025

DBR: Divergence-Based Regularization for Debiasing Natural Language Understanding Models

Zihao Li, Ruixiang Tang, Lu Cheng, Shuaiqiang Wang, Dawei Yin, Mengnan Du

Comments Accepted by SIGKDD Explorations

Collaboration of Large Language Models and Small Recommendation Models for Device-Cloud Recommendation

Zheqi Lv, Tianyu Zhan, Wenjie Wang, Xinyu Lin, Shengyu Zhang, Wenqiao Zhang, Jiwei Li, Kun Kuang, Fei Wu

Comments Published on KDD'25: Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2025

LH-Mix: Local Hierarchy Correlation Guided Mixup over Hierarchical Prompt Tuning

Fanshuang Kong, Richong Zhang, Ziqiao Wang

Comments Accepted by KDD 2025

SWaT: Statistical Modeling of Video Watch Time through User Behavior Analysis

Shentao Yang, Haichuan Yang, Linna Du, Adithya Ganesh, Bo Peng, Boying Liu, Serena Li, Ji Liu

Comments Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1 (KDD '25),

FABind+: Enhancing Molecular Docking through Improved Pocket Prediction and Pose Generation

Kaiyuan Gao, Qizhi Pei, Gongbo Zhang, Jinhua Zhu, Kun He, Lijun Wu

Comments Accepted for presentation at KDD 2025

Fast and Effective GNN Training through Sequences of Random Path Graphs

Francesco Bonchi, Claudio Gentile, Francesco Paolo Nerini, André Panisson, Fabio Vitale

Comments 16 pages, 8 figures; Accepted at KDD 2025

Robust Uplift Modeling with Large-Scale Contexts for Real-time Marketing

Zexu Sun, Qiyu Han, Minqin Zhu, Hao Gong, Dugang Liu, Chen Ma

Comments Accepted to KDD'25 Research Track, 15 pages, 11 figures

Understanding and Mitigating Hyperbolic Dimensional Collapse in Graph Contrastive Learning

Yifei Zhang, Hao Zhu, Menglin Yang, Jiahong Liu, Rex Ying, Irwin King, Piotr Koniusz

Comments This paper is accepted by The 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2025

Beyond the Surface: Uncovering Implicit Locations with LLMs for Personalized Local News

Gali Katz, Hai Sitton, Guy Gonen, Yohay Kaplan

Comments 10 pages, 2 figures, submitted to kdd

DAG: Deep Adaptive and Generative $K$-Free Community Detection on Attributed Graphs

Chang Liu, Yuwen Yang, Yue Ding, Hongtao Lu, Wenqing Lin, Ziming Wu, Wendong Bi

Comments Accepted by SIGKDD 2024

Multi-Branch Collaborative Learning Network for Video Quality Assessment in Industrial Video Search

Hengzhu Tang, Zefeng Zhang, Zhiping Li, Zhenyu Zhang, Xing Wu, Li Gao, Suqi Cheng, Dawei Yin

Comments KDD 2025 ADS

Fairness Driven Slot Allocation Problem in Billboard Advertisement

Dildar Ali, Suman Banerjee, Shweta Jain, Yamuna Prasad

Comments This work has been accepted as a full paper at the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2025)

Counterfactual Explanations with Probabilistic Guarantees on their Robustness to Model Change

Ignacy Stępka, Mateusz Lango, Jerzy Stefanowski

Comments Accepted at 31st SIGKDD Conference on Knowledge Discovery and Data Mining 2025

An Adaptable Budget Planner for Enhancing Budget-Constrained Auto-Bidding in Online Advertising

Zhijian Duan, Yusen Huo, Tianyu Wang, Zhilin Zhang, Yeshu Li, Chuan Yu, Jian Xu, Bo Zheng, Xiaotie Deng

Comments In KDD 2025 ADS Track August

Harnessing Scale and Physics: A Multi-Graph Neural Operator Framework for PDEs on Arbitrary Geometries

Zhihao Li, Haoze Song, Di Xiao, Zhilu Lai, Wei Wang

Comments Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1 (KDD '25)

IN-Flow: Instance Normalization Flow for Non-stationary Time Series Forecasting

Wei Fan, Shun Zheng, Pengyang Wang, Rui Xie, Kun Yi, Qi Zhang, Jiang Bian, Yanjie Fu

Comments Accepted by KDD 2025

AgentGen: Enhancing Planning Abilities for Large Language Model based Agent via Environment and Task Generation

Mengkang Hu, Pu Zhao, Can Xu, Qingfeng Sun, Jianguang Lou, Qingwei Lin, Ping Luo, Saravan Rajmohan

Comments Accepted by KDD 2025 (Research Track). Project page: https://agent-gen.github.io/

Max-Min Diversification with Asymmetric Distances

Iiro Kumpulainen, Florian Adriaens, Nikolaj Tatti

Journal ref Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. (2024) 1440-1450

Combinatorial Optimization Perspective based Framework for Multi-behavior Recommendation

Chenhao Zhai, Chang Meng, Yu Yang, Kexin Zhang, Xuhao Zhao, Xiu Li

Comments Accepted by KDD 2025 Research Track

Fine-tuning Multimodal Large Language Models for Product Bundling

Xiaohao Liu, Jie Wu, Zhulin Tao, Yunshan Ma, Yinwei Wei, Tat-seng Chua

Comments Accepted by KDD 2025 (CR)

A Partial Initialization Strategy to Mitigate the Overfitting Problem in CATE Estimation with Hidden Confounding

Chuan Zhou, Yaxuan Li, Chunyuan Zheng, Haiteng Zhang, Haoxuan Li, Mingming Gong

Comments Presented as a poster in the 2nd Workshop on Causal Inference and Machine Learning in Practice at KDD 2024

Benchmarking and Defending Against Indirect Prompt Injection Attacks on Large Language Models

Jingwei Yi, Yueqi Xie, Bin Zhu, Emre Kiciman, Guangzhong Sun, Xing Xie, Fangzhao Wu

Comments Accepted by KDD 2025

Language Representation Favored Zero-Shot Cross-Domain Cognitive Diagnosis

Shuo Liu, Zihan Zhou, Yuanhao Liu, Jing Zhang, Hong Qian

Journal ref KDD 2025

User Engagement in Mobile Health Applications

Babaniyi Yusuf Olaniyi, Ana Fernández del Río, África Periáñez, Lauren Bellhouse

Comments Accepted at KDD 2022 Health Day, will be appear in the KDD2022 proceedings as a full paper

Journal ref KDD '22: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 4704-4712, 2022

Making Temporal Betweenness Computation Faster and Restless

Filippo Brunelli, Pierluigi Crescenzi, Laurent Viennot

Journal ref KDD '24: The 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Aug 2024, Barcelona, Spain. pp.163-174

A Unified Invariant Learning Framework for Graph Classification

Yongduo Sui, Jie Sun, Shuyao Wang, Zemin Liu, Qing Cui, Longfei Li, Xiang Wang

Comments Accepted to KDD 2025

NoteLLM-2: Multimodal Large Representation Models for Recommendation

Chao Zhang, Haoxin Zhang, Shiwei Wu, Di Wu, Tong Xu, Xiangyu Zhao, Yan Gao, Yao Hu, Enhong Chen

Comments Accepted by KDD'25 ADS track