KDD

Counterfactual Generative Models for Time-Varying Treatments

Shenghao Wu, Wenbin Zhou, Minshuo Chen, Shixiang Zhu

Comments Published at KDD'24

Deep Bag-of-Words Model: An Efficient and Interpretable Relevance Architecture for Chinese E-Commerce

Zhe Lin, Jiwei Tan, Dan Ou, Xi Chen, Shaowei Yao, Bo Zheng

Comments KDD'24 accepted paper

URRL-IMVC: Unified and Robust Representation Learning for Incomplete Multi-View Clustering

Ge Teng, Ting Mao, Chen Shen, Xiang Tian, Xuesong Liu, Yaowu Chen, Jieping Ye

Comments Accepted by ACM SIGKDD 2024

Rethinking Graph Backdoor Attacks: A Distribution-Preserving Perspective

Zhiwei Zhang, Minhua Lin, Enyan Dai, Suhang Wang

Comments Accepted by KDD 2024

From Supervised to Generative: A Novel Paradigm for Tabular Deep Learning with Large Language Models

Xumeng Wen, Han Zhang, Shun Zheng, Wei Xu, Jiang Bian

Comments Accepted by KDD 2024

High-Dimensional Distributed Sparse Classification with Scalable Communication-Efficient Global Updates

Fred Lu, Ryan R. Curtin, Edward Raff, Francis Ferraro, James Holt

Comments KDD 2024, Research Track

Face4RAG: Factual Consistency Evaluation for Retrieval Augmented Generation in Chinese

Yunqi Xu, Tianchi Cai, Jiyan Jiang, Xierui Song

Journal ref KDD 2024 (oral)

EcoVal: An Efficient Data Valuation Framework for Machine Learning

Ayush K Tarun, Vikram S Chundawat, Murari Mandal, Hong Ming Tan, Bowei Chen, Mohan Kankanhalli

Comments KDD-2024

LLM4DyG: Can Large Language Models Solve Spatial-Temporal Problems on Dynamic Graphs?

Zeyang Zhang, Xin Wang, Ziwei Zhang, Haoyang Li, Yijian Qin, Wenwu Zhu

Comments Accepted by ACM KDD'24

JSCDS: A Core Data Selection Method with Jason-Shannon Divergence for Caries RGB Images-Efficient Learning

Peiliang Zhang, Yujia Tong, Chenghu Du, Chao Che, Yongjun Zhu

Comments Accepted in KDD 2024 Workshop AIDSH

Understanding the Ranking Loss for Recommendation with Sparse User Feedback

Zhutian Lin, Junwei Pan, Shangyu Zhang, Ximei Wang, Xi Xiao, Shudong Huang, Lei Xiao, Jie Jiang

Journal ref SIGKDD 2024

Ads Recommendation in a Collapsed and Entangled World

Junwei Pan, Wei Xue, Ximei Wang, Haibin Yu, Xun Liu, Shijie Quan, Xueming Qiu, Dapeng Liu, Lei Xiao, Jie Jiang

Journal ref SIGKDD 2024

Where have you been? A Study of Privacy Risk for Point-of-Interest Recommendation

Kunlin Cai, Jinghuai Zhang, Zhiqing Hong, Will Shand, Guang Wang, Desheng Zhang, Jianfeng Chi, Yuan Tian

Comments 18 pages

Journal ref The 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024)

A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys)

Yashar Deldjoo, Zhankui He, Julian McAuley, Anton Korikov, Scott Sanner, Arnau Ramisa, René Vidal, Maheswaran Sathiamoorthy, Atoosa Kasirzadeh, Silvia Milano

Comments This survey accompanies a tutorial presented at ACM KDD'24

PeFAD: A Parameter-Efficient Federated Framework for Time Series Anomaly Detection

Ronghui Xu, Hao Miao, Senzhang Wang, Philip S. Yu, Jianxin Wang

Comments Accepted by SIGKDD 2024 (Research Track)

Large Scale Hierarchical Industrial Demand Time-Series Forecasting incorporating Sparsity

Harshavardhan Kamarthi, Aditya B. Sasanur, Xinjie Tong, Xingyu Zhou, James Peters, Joe Czyzyk, B. Aditya Prakash

Comments Accepted at KDD 2024

EAGER: Two-Stream Generative Recommender with Behavior-Semantic Collaboration

Ye Wang, Jiahao Xun, Minjie Hong, Jieming Zhu, Tao Jin, Wang Lin, Haoyuan Li, Linjun Li, Yan Xia, Zhou Zhao, Zhenhua Dong

Comments Accepted by KDD 2024. Code available at https://reczoo.github.io/EAGER

Multimodal Pretraining, Adaptation, and Generation for Recommendation: A Survey

Qijiong Liu, Jieming Zhu, Yanting Yang, Quanyu Dai, Zhaocheng Du, Xiao-Ming Wu, Zhou Zhao, Rui Zhang, Zhenhua Dong

Comments Accepted by KDD 2024. See our tutorial materials at https://mmrec.github.io

Reliable Confidence Intervals for Information Retrieval Evaluation Using Generative A.I

Harrie Oosterhuis, Rolf Jagerman, Zhen Qin, Xuanhui Wang, Michael Bendersky

Comments KDD '24

Addressing Prediction Delays in Time Series Forecasting: A Continuous GRU Approach with Derivative Regularization

Sheo Yon Jhin, Seojin Kim, Noseong Park

Comments KDD 2024 accepted paper

COMET: NFT Price Prediction with Wallet Profiling

Tianfu Wang, Liwei Deng, Chao Wang, Jianxun Lian, Yue Yan, Nicholas Jing Yuan, Qi Zhang, Hui Xiong

Comments Accepted by KDD 2024 (ADS Track)

FLea: Addressing Data Scarcity and Label Skew in Federated Learning via Privacy-preserving Feature Augmentation

Tong Xia, Abhirup Ghosh, Xinchi Qiu, Cecilia Mascolo

Comments This paper has been acceped by KDD'24

MARLP: Time-series Forecasting Control for Agricultural Managed Aquifer Recharge

Yuning Chen, Kang Yang, Zhiyu An, Brady Holder, Luke Paloutzian, Khaled Bali, Wan Du

Comments Accepted by KDD 2024

MMBee: Live Streaming Gift-Sending Recommendations via Multi-Modal Fusion and Behaviour Expansion

Jiaxin Deng, Shiyao Wang, Yuchen Wang, Jiansong Qi, Liqin Zhao, Guorui Zhou, Gaofeng Meng

Comments Accepted at KDD 2024

FoRAG: Factuality-optimized Retrieval Augmented Generation for Web-enhanced Long-form Question Answering

Tianchi Cai, Zhiwen Tan, Xierui Song, Tao Sun, Jiyan Jiang, Yunqi Xu, Yinger Zhang, Jinjie Gu

Journal ref KDD 2024

UniST: A Prompt-Empowered Universal Model for Urban Spatio-Temporal Prediction

Yuan Yuan, Jingtao Ding, Jie Feng, Depeng Jin, Yong Li

Comments 2024 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2024

Personalized Federated Continual Learning via Multi-granularity Prompt

Hao Yu, Xin Yang, Xin Gao, Yan Kang, Hao Wang, Junbo Zhang, Tianrui Li

Comments Accepted by KDD 2024 Research Track

Adapting Job Recommendations to User Preference Drift with Behavioral-Semantic Fusion Learning

Xiao Han, Chen Zhu, Xiao Hu, Chuan Qin, Xiangyu Zhao, Hengshu Zhu

Comments Accepted by KDD 24 Research Track

Diverse Intra- and Inter-Domain Activity Style Fusion for Cross-Person Generalization in Activity Recognition

Junru Zhang, Lang Feng, Zhidan Liu, Yuhan Wu, Yang He, Yabo Dong, Duanqing Xu

Comments The 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024)

Topology-aware Embedding Memory for Continual Learning on Expanding Networks

Xikun Zhang, Dongjin Song, Yixin Chen, Dacheng Tao

Comments This paper has been accepted by KDD 2024