Feature Interaction Modeling

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Overview

Feature interaction modeling studies how the effect of one input depends on other inputs, allowing models to capture combinations that additive methods miss. It matters in settings such as recommendation, tabular prediction, forecasting, and scientific data analysis, where useful signals may arise from feature combinations rather than individual variables. Common approaches include multiplicative or tensor-based interactions, attention and token mixing, selective interaction layers, and interpretable decompositions using GAMs, ANOVA, or Shapley methods. A central tension is how to recover meaningful higher-order structure without introducing spurious interactions, excessive computation, or explanations that fail under correlated or limited data.

Latest papers

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71 papers11 papers in the last four weeks, up 38% on the four weeks before. 0.1% of all new papers.

  1. Hierarchical Multimodal Interaction Reasoning for Dyadic Relationship Recognition

    Oct 26, 2026Wang Tang, Fethiye Irmak Dogan, Linbo Qing +2Relational ReasoningMultimodal Reasoning

    School of Software Engineering, Chengdu University of Information Technology, Chengdu 610103, China · AFAR Lab, Department of Computer Science and Technology, University of Cambridge, CB3 0FT Cambridge, U.K. · College of Electronics and Information Engineering, Sichuan University, Chengdu 610065, China +1

  2. Beyond feature attribution: Recovering latent interaction structures in machine learning models via localized CBFI

    Oct 26, 2026Sejong OhFeature AttributionFeature Interaction Modeling

    Department of Software Science, Dankook University, Gyeonggi-do, Republic of Korea

  3. EASformer: Environment-Action-State Alignment for Industrial Generative Ranking

    Oct 20, 2026Bohao Li, DingLun Cao, Pengcheng Huang +11Learning to RankGenerative Recommendation

    Beihang University, Beijing, China · Harbin Institute of Technology, Shenzhen, China · Independent Researcher, Shanghai, China +1

  4. Predictive Closure: A Set-Level Characterization of JEPA's Feature Selection

    Oct 19, 2026Mosh Levy, Aly Lidayan, Yoav GoldbergJoint-Embedding Predictive ArchitecturePredictive Representation Learning

    Bar-Ilan University · University of California, Berkeley · Allen Institute for AI

  5. A Multi-granularity Interaction Network for Relational Triple Extraction

    Oct 18, 2026Xiaocheng Luo, Yanping Chen, Zaifu ZhanRelation ExtractionFeature Interaction Modeling

    School of Computer Science and Technology, Soochow University, Suzhou, 215006, Jiangsu, PR China · State Key Laboratory of Public Big Data, College of Computer Science and Technology, Guizhou University, Guiyang, 550025, Guizhou, PR China · Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, 55455, MN, USA

  6. Behavioral Compositionality of Sparse Autoencoder Representations

    Oct 15, 2026Haotian Ma, Ziye Mei, Frederic SalaSparse AutoencodersCompositional Representation Learning

    Department of Computer Sciences, University of Wisconsin–Madison

  7. Predicting Unseen Scientific Interactions: Conditional Flow Models Hallucinate Non-Additive Effects

    Oct 14, 2026Sam Gijsen, Moritz Seiler, Kerstin RitterConditional Generative ModelingFeature Interaction Modeling

  8. Graph Additive Models disentangling feature, topology, and interactions

    Oct 14, 2026Clara Alvarez-Rodriguez, Steve Azzolin, Vincenzo Marco De Luca +3Graph Neural NetworksGNN Explainability

    The Arctic University of Norway

  9. Better Capturing Interactions Between Products inRetail: Revisited Negative Sampling forBasket Choice Modeling

    Oct 13, 2026Jules Désir, Vincent Auriau, Martin Možina +1Discrete Choice ModelingFeature Interaction Modeling

    Artefact Research Center, Paris, France · MICS, CentraleSupélec Université Paris-Saclay, Gif-sur-Yvette, France · Fortenova Group, Zagreb, Croatia

  10. RelICL: Training-free Relational Learning with Tabular Foundation Models

    Oct 1, 2026Simon Forbat, Rainer GemullaTabular Foundation ModelsFeature Interaction Modeling

    Data and Web Science Group University of Mannheim Mannheim, Germany

  11. Beyond Interaction Capacity: Estimator Scaling with Recursive Models for CTR Prediction

    Sep 29, 2026Shivang Chopra, Fotis Iliopoulos, Zsolt Kira +1Feature Interaction ModelingEnsemble Learning

    Georgia Institute of Technology · Google Research

  12. Correction-space Cross-variate Interaction for Test-time Adaptation in Time Series Forecasting

    Sep 28, 2026Yuanyuan Deng, Mykola Pechenizkiy, Songgaojun DengMultivariate Time Series ForecastingFeature Interaction Modeling

    Eindhoven University of Technology Eindhoven, The Netherlands

  13. Cardinality-Stratified Interaction Decomposition for Interpretable Pairwise and Higher-Order Structure in Transactional Basket Data

    Sep 28, 2026Hidetoshi Kawase, Toshihiro OtaFeature Interaction ModelingData Association

    CyberAgent, Inc., Shibuya, Tokyo 150–6121 Japan

  14. When Does Synergy Help Active Feature Acquisition? A PID-Based Study

    Sep 26, 2026Jie Li, Maruf A. Dhali, Hjalmar R. BoumaActive Feature AcquisitionFeature Interaction Modeling

    Acutelines Data Science Group University Medical Center Groningen University of Groningen Groningen, The Netherlands · Department of Artificial Intelligence University of Groningen Groningen, The Netherlands

  15. QueryFormer: Winning Solution for KDD Cup 2026 Tencent UniRec Challenge

    Sep 15, 2026Yuanzhe Zhou, Zhaoyang ZengConversion Rate PredictionUser Modeling

    Wuhan University · Sun Yat-sen University

  16. Typed Temporal Interaction Features for Simulation-Backed Forecasting of Open-Source Game Release Incidents

    Sep 12, 2026Shayma Alkobaisi, Anas AliFeature Interaction Modeling

    Department of Computer Science and Software Engineering, United Arab Emirates University, Al Ain, United Arab Emirates · Department of Computer Science, National University of Modern languages, Lahore, Pakistan

  17. Synergistic Fusion of Topological Structure and Temporal Semantics of Mobility for Urban Region Embedding

    Sep 8, 2026Namwoo Kim, Jeeyun Chang, Kanghoon Lee +1Feature Interaction ModelingGeospatial Representation Learning

    Urban AI Institute, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea · Graduate School of Data Science, KAIST, Daejeon, Republic of Korea · Department of Industrial Engineering and Systems, KAIST, Daejeon, Republic of Korea +1

  18. Temporal Heterogeneous Graph Transformer for Credit Card Fraud Detection

    Sep 7, 2026Qinwen YanFinancial Fraud DetectionTransformer

    University of California, Los Angeles Los Angeles, California, USA

  19. Event Interaction in Low-Rank Bottlenecks for Temporal Relation Extraction

    Sep 6, 2026Wei Sun, Tingyu Qu, Jesse Davis +1Relation ExtractionFeature Interaction Modeling

    Department of Computer Science, KU Leuven Celestijnenlaan 200A 3001 Heverlee, Belgium

  20. How Does Parameter Pruning Reshape DNN Representations? An Interaction-Driven Exploration

    Sep 6, 2026Fangbo Li, Junpeng Zhang, Qihan Ren +1Neural Network PruningNeural Network Interpretability

  21. From Feature Interaction to Feature Transport - A Unified Block for Scalable Recommendation Models

    Aug 31, 2026Zichen Luo, Jiachen Guo, Keming Gu +1Recommender SystemsFeature Interaction Modeling

    Tianjin University Jinnan Qu, Tianjin Shi, China

  22. Advancing Interaction-Sensitive Feature Selection: Novel Relief-Based Algorithms, Expanded Comparisons, and Recommendations for Biomedical Data Mining

    Aug 28, 2026Kia Kazemi-Nia, Harsh Bandhey, Philip J. Freda +1Feature SelectionFeature Interaction Modeling

    Cedars-Sinai Health Sciences University, Los Angeles, 90048, CA, USA

  23. When Similarity Is Interaction-Driven: Quantum Kernels for Regime-Sensitive Learning

    Aug 25, 2026Hanqiu Peng, Jianlong Lu, Ying ChenQuantum Feature MapsFeature Interaction Modeling

    Centre for Quantitative Finance, Department of Mathematics Risk Management Institute, National University of Singapore, Singapore

  24. TabNSM: Neural Sparse Mixer for Tabular Regression

    Aug 18, 2026Ali Eslamian, Qiang ChengTabular RegressionTabular Representation Learning

    Department of Computer Science University of Kentucky Lexington, KY 40506 · Department of Computer Science Institute for Biomedical Informatics University of Kentucky Lexington, KY 40506

  25. UniDot: A Unified Network for Sequence Modeling and Feature Interaction in Large-scale Recommendation

    Aug 17, 2026Rongcheng Lin, Yan Sun, Jamey Zhang +4Recommender SystemsFeature Interaction Modeling

    Meta Menlo Park, USA

  26. Feature Interaction Modeling for Neural Operators

    Jul 30, 2026Quan Gu, Xiaoduo Li, Hongxia LiuFeature Interaction ModelingPDE Surrogate Modeling

    Independent Researcher · Taiyuan University of Technology

  27. ANFI: Rethinking Neighbor Feature Interaction in Person Re-ID

    Jul 28, 2026Xulin Li, Yan Lu, Bin Liu +5Feature Interaction ModelingPerson Re-Identification

    University of Science and Technology of China, China · Anhui Province Key Laboratory of Digital Security, China · The Chinese University of Hong Kong, China

  28. The Quadrilateral Loss: Additivity as a Measurable Behavior of Dense Neural Networks

    Jul 22, 2026Antonio Di CeccoFeature Interaction ModelingNeural Network Interpretability

    Universit`a "G. d'Annunzio" Chieti–Pescara, and School of AI.

  29. BRIDGE: Bottleneck-Aware Regulator-Set Inference and Diagnosis for Cooperative Gene Regulatory Recovery

    Jul 21, 2026Maryam Rahimimovassagh, Clayton Thomas Barham, Ivan Garibay +1Feature Interaction ModelingGene Regulatory Network Inference

    University of Central Florida

  30. WHALE: A Scalable Unified Model for Recommendation with Wukong-HSTU Architecture

    Jul 19, 2026Renqin Cai, Dawei Sun, Yuanjun Yao +8Sequential RecommendationFeature Interaction Modeling

    Meta Platforms, Inc. USA