Automated Label Placement on Maps via Large Language Models
机构 * University of Texas at Arlington（德克萨斯理工大学） ； HRL Laboratories（HRL实验室）
Comments Workshop on AI for Data Editing (AI4DE) at KDD 2025
期刊&会议
KDD
ACM SIGKDD Conference on Knowledge Discovery and Data Mining · 会议 · Data Mining
Harnessing the Power of Interleaving and Counterfactual Evaluation for Airbnb Search Ranking
机构 * Microsoft（微软）
Comments 10 pages
Journal ref Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2 (KDD 2025)
EVINET: Towards Open-World Graph Learning via Evidential Reasoning Network
机构 * Virginia Polytechnic Institute and State University（弗吉尼亚理工大学） ； University of Rochester（罗切斯特大学） ； Wayne State University（韦恩州立大学）
Comments KDD 2025
Tackling Size Generalization of Graph Neural Networks on Biological Data from a Spectral Perspective
机构 * University of Illinois Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校） ； University of Michigan, Ann Arbor（密歇根大学安娜堡分校） ； Dartmouth College（达特茅斯学院）
Comments KDD 2025
Constructing and Sampling Directed Graphs with Linearly Rescaled Degree Matrices
Comments SIGKDD 2022
A Graph-based Approach for Multi-Modal Question Answering from Flowcharts in Telecom Documents
机构 * Ericsson R&D Bangalore Karnataka India（爱立信研发部班加罗尔卡纳塔克邦印度）
Comments Accepted for publication at the KDD 2025 Workshop on Structured Knowledge for Large Language Models
How and Where to Translate? The Impact of Translation Strategies in Cross-lingual LLM Prompting
机构 * Amazon（亚马逊）
Comments Accepted at Prompt Optimization KDD '25
Self-Regularization with Sparse Autoencoders for Controllable LLM-based Classification
机构 * University of Georgia（佐治亚大学） ； Tencent AI Lab（腾讯AI实验室）
Comments Accepted by SIGKDD 2025
Quantizing Text-attributed Graphs for Semantic-Structural Integration
机构 * Singapore Management University（新加坡国立管理大学） ； Beijing Normal University（北京师范大学）
Comments Accepted at KDD'2025
Agent0: Leveraging LLM Agents to Discover Multi-value Features from Text for Enhanced Recommendations
机构 * Teads
Comments Agent4IR, KDD '25
Reasoning Beyond the Obvious: Evaluating Divergent and Convergent Thinking in LLMs for Financial Scenarios
机构 * Deep Insight Labs（深洞察实验室）
Comments Accepted by Agentic & GenAI Evaluation KDD2025: KDD workshop on Evaluation and Trustworthiness of Agentic and Generative AI Models https://kdd-eval-workshop.github.io/genai-evaluation-kdd2025/
Hyperbolic Deep Learning for Foundation Models: A Survey
机构 * Yale University（耶鲁大学） ； Hong Kong University of Science（香港科学大学）
Comments 11 Pages, SIGKDD 2025
T-GRAB: A Synthetic Diagnostic Benchmark for Learning on Temporal Graphs
机构 * Mila ； DIRO-UdeM ； University of Oxford（牛津大学） ； SoCS-McGill（麦吉尔大学社会学与计算机科学系） ； CIFAR AI Chair（CIFAR人工智能主席）
Comments Accepted to MLoG-GenAI Workshop @ KDD 2025 (Oral)
DeRAG: Black-box Adversarial Attacks on Multiple Retrieval-Augmented Generation Applications via Prompt Injection
机构 * Department of Management Information Systems, National ChengChi University（管理信息系，国立中正大学）
Comments Accepted by KDD Workshop on Prompt Optimization 2025
Hierarchical Prompting Taxonomy: A Universal Evaluation Framework for Large Language Models Aligned with Human Cognitive Principles
机构 * Indian Institute of Technology Kharagpur（印度理工学院Khargapur分校） ； Rochester Institute of Technology（罗切斯特理工学院） ； Researcher, Fatima Fellowship（研究员，Fatima fellowship） ； AI Institute, University of South Carolina（人工智能研究所，南卡罗来纳大学） ； Amazon GenAI（亚马逊生成人工智能） ； Stanford University（斯坦福大学） ； James Silberrad Brown Center for AI, San Diego State University（詹姆斯·西伯拉德·布朗人工智能中心，圣地亚哥州立大学）
Comments 18 pages, 9 figures, KDD workshop on Prompt Optimization 2025
RL4CO: an Extensive Reinforcement Learning for Combinatorial Optimization Benchmark
机构 * Leuphana University（吕贝克大学） ； MIT（麻省理工学院） ； Southeast University（东南大学） ； Peking University（北京大学） ； Bielefeld University（比勒菲尔德大学） ； Nanyang Technological University（南洋理工大学） ； Soochow University（苏州大学） ； City University of Hong Kong（香港城市大学） ； University of Brescia（布雷西亚大学） ； ORTEC（ORTEC公司） ； Singapore Management University（新加坡管理学院） ； Brandenburg University of Technology（勃兰登堡技术大学）
Comments KDD 2025 Oral
Self-Tuning Self-Supervised Image Anomaly Detection
机构 * Carnegie Mellon University（卡内基梅隆大学）
Comments Accepted to KDD 2025
Positive-Unlabeled Learning for Control Group Construction in Observational Causal Inference
机构 * Artificial Intelligence Group, Wageningen University and Research（瓦赫宁根大学与研究所人工智能组） ； BEYOND Centre, National Observatory of Athens（雅典国家天文台BEYOND中心） ； Image Processing Laboratory (IPL), University of Valencia（瓦伦西亚大学图像处理实验室（IPL））
Comments Accepted at KDD 2025 Workshop on Causal Inference and Machine Learning in Practice
Text-to-SQL for Enterprise Data Analytics
机构 * LinkedIn（领英）
Comments 11 pages, 8 figures, Workshop on Agentic AI for Enterprise at KDD '25
Improving Group Robustness on Spurious Correlation via Evidential Alignment
机构 * University of Virginia（弗吉尼亚大学）
Comments Accepted at KDD 2025 (Research Track)
PMKLC: Parallel Multi-Knowledge Learning-based Lossless Compression for Large-Scale Genomics Database
Comments Accepted via KDD-25
Timing is Important: Risk-aware Fund Allocation based on Time-Series Forecasting
机构 * McGill University \& MILA - Quebec AI Institute Montreal Canada ； McGill University Montreal Canada ； FiT, Tencent Shenzhen China ； College of Big Data ； Internet\ Technology University Shenzhen China ； McGill University \& MILA - Quebec AI Institute ； McGill University ； FiT, Tencent ； Internet\ Technology University
Comments Accepted by KDD 2025 ADS Track
Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows
机构 * ServiceNow
Comments 8 pages, 7 figures. Accepted to Workshop on Structured Knowledge for Large Language Models (SKnowLLM) at KDD 2025
Multi-task retriever fine-tuning for domain-specific and efficient RAG
机构 * ServiceNow
Comments 7 pages, 2 figures. Accepted at Workshop on Structured Knowledge for Large Language Models (SKnowLLM) at KDD 2025
Towards Understanding Link Predictor Generalizability Under Distribution Shifts
机构 * Michigan State University（密歇根州立大学）
Comments KDD 25' Datasets & Benchmarks Track, 14 pages, 8 figures, 18 tables
CLID-MU: Cross-Layer Information Divergence Based Meta Update Strategy for Learning with Noisy Labels
机构 * Worcester Polytechnic Institute（沃斯特理工学院）
Comments KDD 2025, 12 pages, 7 figures
Measuring Spiritual Values and Bias of Large Language Models
机构 * Department of Computer Science（计算机科学系） ； Center for Data Science, School of Nursing（数据科学中心、护理学院） ； Department of Religion（宗教系） ； Emory University（埃默里大学）
Comments 9 pages including appendix; 5 figures; 5 tables
Journal ref in Proceedings of KDD 2025 SciSoc LLM Workshop
Outbound Modeling for Inventory Management
机构 * Amazon – SCOT Inbound Systems（亚马逊-SCOT入仓系统） ； Amazon AWS – NeuroSymbolic AI（亚马逊AWS-神经符号AI）
Comments KDD - AI for Supply Chain Workshop
TAT: Temporal-Aligned Transformer for Multi-Horizon Peak Demand Forecasting
机构 * Georgia Institute of Technology（佐治亚理工学院） ； Amazon（亚马逊公司）
Comments 9 pages, 4 figures, 7 tables, published at KDD 2025 workshop on AI for Supply Chain: Today and Future
Coordinated Communication and Inventory Optimization in Multi-Retailer Supply Chains
Comments Accepted at the Workshop on "AI for Supply Chain: Today and Future" @ 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2 (KDD '25), August 3, 2025, Toronto, ON, Canada
