KDD

Localised Adaptive Spatial-Temporal Graph Neural Network

Wenying Duan, Xiaoxi He, Zimu Zhou, Lothar Thiele, Hong Rao

Comments This paper was accepted by KDD 2023

I'm Afraid I Can't Do That: Predicting Prompt Refusal in Black-Box Generative Language Models

Max Reuter, William Schulze

Comments Submitted for review to KDD 2023 via the workshop "Foundations and Applications in Large-scale AI Models: Pre-training, Fine-tuning, and Prompt-based Learning"

Revisiting Hate Speech Benchmarks: From Data Curation to System Deployment

Atharva Kulkarni, Sarah Masud, Vikram Goyal, Tanmoy Chakraborty

Comments 15 pages, 4 figures, 11 tables. Accepted at SIGKDD'23

Road Planning for Slums via Deep Reinforcement Learning

Yu Zheng, Hongyuan Su, Jingtao Ding, Depeng Jin, Yong Li

Comments Conference version of this paper published in KDD'23

Improving Training Stability for Multitask Ranking Models in Recommender Systems

Jiaxi Tang, Yoel Drori, Daryl Chang, Maheswaran Sathiamoorthy, Justin Gilmer, Li Wei, Xinyang Yi, Lichan Hong, Ed H. Chi

Comments Accepted at KDD 2023; 12 pages

AdaProp: Learning Adaptive Propagation for Graph Neural Network based Knowledge Graph Reasoning

Yongqi Zhang, Zhanke Zhou, Quanming Yao, Xiaowen Chu, Bo Han

Comments accepted by KDD 2023

Reducing Exposure to Harmful Content via Graph Rewiring

Corinna Coupette, Stefan Neumann, Aristides Gionis

Comments 25 pages, 28 figures, accepted at KDD 2023

Skill Disentanglement for Imitation Learning from Suboptimal Demonstrations

Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen

Journal ref Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '23), August 6--10, 2023, Long Beach, CA, USA

WebGLM: Towards An Efficient Web-Enhanced Question Answering System with Human Preferences

Xiao Liu, Hanyu Lai, Hao Yu, Yifan Xu, Aohan Zeng, Zhengxiao Du, Peng Zhang, Yuxiao Dong, Jie Tang

Comments Accepted to KDD 2023

FIRE: An Optimization Approach for Fast Interpretable Rule Extraction

Brian Liu, Rahul Mazumder

Journal ref Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023)

DyGen: Learning from Noisy Labels via Dynamics-Enhanced Generative Modeling

Yuchen Zhuang, Yue Yu, Lingkai Kong, Xiang Chen, Chao Zhang

Comments Accepted by KDD 2023 research track

Causal Inference via Style Transfer for Out-of-distribution Generalisation

Toan Nguyen, Kien Do, Duc Thanh Nguyen, Bao Duong, Thin Nguyen

Comments In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 23), August 6-10, 2023, Long Beach, CA, USA. ACM, New York, NY, USA, 19 pages

Journal ref In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 23), August 6-10, 2023, Long Beach, CA, USA. ACM, New York, NY, USA, 19 pages

SoccerCPD: Formation and Role Change-Point Detection in Soccer Matches Using Spatiotemporal Tracking Data

Hyunsung Kim, Bit Kim, Dongwook Chung, Jinsung Yoon, Sang-Ki Ko

Journal ref Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2022

On Improving the Cohesiveness of Graphs by Merging Nodes: Formulation, Analysis, and Algorithms

Fanchen Bu, Kijung Shin

Comments The extended version of the KDD 2023 paper with the same title; 33 pages, 12 figures, 9 tables

SentiGOLD: A Large Bangla Gold Standard Multi-Domain Sentiment Analysis Dataset and its Evaluation

Md. Ekramul Islam, Labib Chowdhury, Faisal Ahamed Khan, Shazzad Hossain, Sourave Hossain, Mohammad Mamun Or Rashid, Nabeel Mohammed, Mohammad Ruhul Amin

Comments Accepted in KDD 2023 Applied Data Science Track; 12 pages, 14 figures

Virtual Node Tuning for Few-shot Node Classification

Zhen Tan, Ruocheng Guo, Kaize Ding, Huan Liu

Comments Accepted to KDD 2023

RankFormer: Listwise Learning-to-Rank Using Listwide Labels

Maarten Buyl, Paul Missault, Pierre-Antoine Sondag

Comments Accepted at KDD 2023

Generalizable Low-Resource Activity Recognition with Diverse and Discriminative Representation Learning

Xin Qin, Jindong Wang, Shuo Ma, Wang Lu, Yongchun Zhu, Xing Xie, Yiqiang Chen

Comments Accepted by SIGKDD 2023 Research track; 12 pages; Code is available at: https://github.com/microsoft/robustlearn

Towards Fairness in Personalized Ads Using Impression Variance Aware Reinforcement Learning

Aditya Srinivas Timmaraju, Mehdi Mashayekhi, Mingliang Chen, Qi Zeng, Quintin Fettes, Wesley Cheung, Yihan Xiao, Manojkumar Rangasamy Kannadasan, Pushkar Tripathi, Sean Gahagan, Miranda Bogen, Rob Roudani

Comments 11 pages, 7 figure, KDD 2023

Generative Flow Network for Listwise Recommendation

Shuchang Liu, Qingpeng Cai, Zhankui He, Bowen Sun, Julian McAuley, Dong Zheng, Peng Jiang, Kun Gai

Comments 11 pages, 5 figures, 7 tables

Journal ref KDD '23, August 6-10, 2023, Long Beach, CA, USA

ExplainableFold: Understanding AlphaFold Prediction with Explainable AI

Juntao Tan, Yongfeng Zhang

Comments This work has been accepted for presentation at the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023)

ShuttleSet: A Human-Annotated Stroke-Level Singles Dataset for Badminton Tactical Analysis

Wei-Yao Wang, Yung-Chang Huang, Tsi-Ui Ik, Wen-Chih Peng

Comments KDD 2023. Project page: https://github.com/wywyWang/CoachAI-Projects

UA-FedRec: Untargeted Attack on Federated News Recommendation

Jingwei Yi, Fangzhao Wu, Bin Zhu, Jing Yao, Zhulin Tao, Guangzhong Sun, Xing Xie

Comments Accepted by KDD 2023

Revisiting Neural Retrieval on Accelerators

Jiaqi Zhai, Zhaojie Gong, Yueming Wang, Xiao Sun, Zheng Yan, Fu Li, Xing Liu

Comments To appear in the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023)

Efficient Centrality Maximization with Rademacher Averages

Leonardo Pellegrina

Comments Accepted to KDD '23

Criteria Tell You More than Ratings: Criteria Preference-Aware Light Graph Convolution for Effective Multi-Criteria Recommendation

Jin-Duk Park, Siqing Li, Xin Cao, Won-Yong Shin

Comments 12 pages, 10 figures, 5 tables; 29th ACM SIGKDD Conference on Knowledge Discovery & Data (KDD 2023) (to appear) (Please cite our conference version.)

Web-Scale Academic Name Disambiguation: the WhoIsWho Benchmark, Leaderboard, and Toolkit

Bo Chen, Jing Zhang, Fanjin Zhang, Tianyi Han, Yuqing Cheng, Xiaoyan Li, Yuxiao Dong, Jie Tang

Comments Accepted by KDD 2023 ADS track

Navigating Alignment for Non-identical Client Class Sets: A Label Name-Anchored Federated Learning Framework

Jiayun Zhang, Xiyuan Zhang, Xinyang Zhang, Dezhi Hong, Rajesh K. Gupta, Jingbo Shang

Comments Accepted by KDD 2023

A Lightweight, Efficient and Explainable-by-Design Convolutional Neural Network for Internet Traffic Classification

Kevin Fauvel, Fuxing Chen, Dario Rossi

Comments Accepted for publication in the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Long Beach, USA, 2023

Classification of Edge-dependent Labels of Nodes in Hypergraphs

Minyoung Choe, Sunwoo Kim, Jaemin Yoo, Kijung Shin

Comments Accepted to KDD 2023