Causal Structure Learning

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14 papers in the last four weeks, with none the four weeks before. 0.1% of all new papers.

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  1. CaSPECT: Discovering Causally Homogeneous Subgroups via Directed Spectral Clustering

    Jul 3, 2026Arghya Pratihar, Shinjon Chakraborty, Swagatam DasCausal Effect EstimationCausal Structure Learning

    1*Electronics and Communication Sciences Unit, Indian Statistical Institute, India. · 2Indian Statistical Institute, India.

  2. Characterizing and Identifying Separable Graphical Models

    Jul 1, 2026Christopher Meek, Kayvan SadeghiCausal Structure LearningProbabilistic Graphical Models

    Department of Statistics, University of Washington · Department of Statistical Science, University College London

  3. Additive Causal Construction for Transferable and Reconfigurable Cross-System Learning in Multi-Source Image Fusion

    Jun 30, 2026Zhizhong Fu, Wei Zhou, Zhaoyang Jiang +5Multi-Source Image FusionCausal Representation Learning

    School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China. · Department of Radiology, Huzhou Maternity & Child Health Care Hospital, Huzhou 313000, China. · Department of Radiology, Huzhou Maternity & Child Health Care Hospital Affiliated to Huzhou Normal University,Huzhou 313000,China. +3

  4. Disentangling Continuous-Time Latent Dynamics: Identifiability of Latent SDEs via Diffusion Shifts

    Jun 26, 2026Yuanyuan Wang, Wenjie Wang, Haoxuan Li +2Stochastic Differential EquationsCausal Representation Learning

    Mohamed bin Zayed University of Artificial Intelligence · The University of Melbourne · Peking University +1

  5. A Causal Foundation Model for Structure and Outcome Prediction

    Jun 25, 2026Max Zhu, Martino Mansoldo, Ching-Hao Wang +1Causal Foundation ModelsCausal Structure Learning

    University of Cambridge, United Kingdom · GSK.ai.

  6. Words as Difference Makers: How Large Language Models Determine Causal Structure in Text

    Jun 21, 2026Wolfgang PietschCausal World ModelsLLM Interpretability

    tum

  7. A Framework for Directed Acyclic Hypergraph Learning

    Jun 19, 2026Zhiyuan Dong, Carlos Mundo-Levano, Wei Qian +2Structural Causal ModelsCausal Structure Learning

    Institute for Financial Services Analytics, University of Delaware, Newark, DE 19716, USA · Department of Electrical and Computer Engineering, University of Delaware, Newark, DE 19716, USA · Department of Applied Economics AND Statistics, University of Delaware, Newark, DE 19716, USA +1

  8. DCD-PFN: A Decoupling-Aware Foundation Model for Causal Discovery

    Jun 19, 2026Zhengkang Guan, Yikang Chen, Yi He +5Causal Foundation ModelsStructural Causal Models

    College of Computer Science and Technology Zhejiang University

  9. Fast Nonparametric Conditional Independence Testing via Two-Stage Regression

    Jun 16, 2026Eric V. StroblCausal DiscoveryCausal Structure Learning

    Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA 15213, USA

  10. From Prompts to Tokens: Internalizing Causal Supervision in Vision-Language Model for Multi-Image Causal Reasoning

    Jun 10, 2026Haoping Yu, Yuanxi Li, Jing MaVisual ReasoningCausal Structure Learning

    Department of Computer & Data Sciences, Case Western University, Cleveland, OH, US.

  11. Causal Ensemble Agent: Hierarchical Causal Discovery with LLM-guided Expert Reweighting

    Jun 9, 2026Xinyu Li, Yuanyuan Wang, Haoxuan Li +7Causal DiscoveryCausal Structure Learning

    The University of Melbourne · MBZUAI · Peking University +4

  12. KG-SoftMAP: Soft Knowledge-Graph Priors for Bayesian Network Structure Learning from Sparse Discrete Data

    Jun 9, 2026Guoliang Xu, James E. CorterGraph Structure LearningBayesian Networks

    Columbia University

  13. polyDAG: Polynomial Acyclicity Constraints for Efficient Continuous Causal Discovery in Visual Semantic Graphs

    Jun 5, 2026Wenhao Zhang, Ramin Ramezani, Tao Han +2Causal DiscoveryCausal Structure Learning

    School of Automation and Intelligent Sensing (Zhang, Han) and School of Computer Science (Guo), Shanghai Jiao Tong University, Shanghai, China · Department of Computer Science, University of California, Los Angeles, CA, USA · The Chinese University of Hong Kong, Shenzhen, China

  14. LLM Explainability with Counterfactual Chains and Causal Graphs

    Jun 4, 2026Nirit Nussbaum-Hoffer, Nitay Calderon, Liat Ein-Dor +1LLM Reasoning with GraphsLLM Interpretability

    Faculty of Data and Decision Sciences, Technion · IBM Research

  15. EML-CD: Causal Mechanism Recovery via EML Symbolic Trees in Structure Learning

    Jun 4, 2026Sota AsanumaStructural Causal ModelsCausal Structure Learning

    SoftBank Corp.

  16. Causal Modeling of Selection in Evolution

    Jun 4, 2026Haoyue Dai, Zeyu Tang, Peter Spirtes +1Structural Causal ModelsCausal Discovery

    Carnegie Mellon University · Stanford University · Mohamed bin Zayed University of Artificial Intelligence

  17. Preserving Data Privacy in Learning Causal Structure with Fully Homomorphic Encryption

    Jun 3, 2026Jian Yang, Yuan Tong, Qinbin Li +2Causal DiscoveryCausal Structure Learning

    Hong Kong University of Science and Technology (Guangzhou) · Hong Kong University of Science and Technology · University of California, Berkeley

  18. Trivium: Temporal Regret as a First-Class Objective for Causal-Memory Controllers

    Jun 3, 2026Edward Y. ChangLifelong Learning AgentsCausal Structure Learning

    Computer Science Stanford University

  19. Identifiable Markov Switching Models with Instantaneous Effects and Exponential Families

    Jun 1, 2026Roel Hulsman, Carles Balsells-Rodas, Sara MagliacaneTime-Series Causal DiscoveryRegime-Switching Dynamical Systems

    University of Amsterdam · 2Adyen · 3Imperial College London +1

  20. Iterative Causal Discovery: Per-Edge Impossibility Certificates, Tier-Aware Oracle Queries, and the 1+K1+K Lower Bound

    May 26, 2026Eichi UeharaBayesian NetworksCausal Discovery

    aflo, Inc., Tokyo, Japan

  21. Evolving Causal Regulatory Networks (ECR-Net)

    May 24, 2026Govind Vallabhasseri Binish, Abdhul Ahadh, Rano Roy Kavanal +1Structural Causal ModelsCausal Discovery

  22. Learning Causal Orderings for In-Context Tabular Prediction

    May 21, 2026Sascha Xu, Sarah Mameche, Jilles VreekenIncomplete Data ImputationCausal Structure Learning

    CISPA Helmholtz Center

  23. Score-Based Causal Discovery of Latent Variable Causal Models

    May 19, 2026Ignavier Ng, Xinshuai Dong, Haoyue Dai +3Latent Variable ModelsStructural Causal Models

    Carnegie Mellon University · University of California, San Diego · Mohamed bin Zayed University of Artificial Intelligence

  24. Exploiting Non-Negativity in DAG Structure Learning

    May 19, 2026Samuel Rey, Madeline navarro, Gonzalo MateosGraph Structure LearningStructural Causal Models

    Dept. of Signal Theory and Communications, Universidad Rey Juan Carlos, Madrid, Spain · Dept. of Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA · Dept. of Electrical and Computer Engineering, University of Rochester, Rochester, NY 14627, USA

  25. A Unified Framework for Structure-Aware Clustering and Heterogeneous Causal Graph Learning

    May 19, 2026Honglin Du, Muxuan Liang, Xiang ZhongStructural Causal ModelsClustering

    Department of Industrial and Systems Engineering, University of Florida, Gainesville, FL 32611, USA · Department of Biostatistics, MD Anderson Cancer Center, Houston, TX 77030, USA

  26. TriOpt: A Scalable Algorithm for Linear Causal Discovery

    May 17, 2026Rafat Ashraf Joy, Elena ZhelevaStructural Causal ModelsCausal Discovery

    University of Illinois Chicago

  27. PACER: Acyclic Causal Discovery from Large-Scale Interventional Data

    May 14, 2026Ramon Viñas Torné, Sílvia Fàbregas Salazar, Soyon Park +4Causal DiscoveryCausal Structure Learning

    Swiss Federal Technology Institute of Lausanne (EPFL), Switzerland · ETH Zurich, Zurich, Switzerland · Cornell University, USA

  28. A Recursive Decomposition Framework for Causal Structure Learning in the Presence of Latent Variables

    May 11, 2026Zheng Li, Feng Xie, Shenglan Nie +3Causal DiscoveryCausal Structure Learning

    Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China · Department of Applied Statistics, Beijing Technology and Business University, Beijing, China · College of Computer Science and Artificial Intelligence, Fudan University, Shanghai, China

  29. Coarsening Linear Non-Gaussian Causal Models with Cycles

    May 11, 2026Francisco Madaleno, Francisco C Pereira, Alex MarkhamStructural Causal ModelsCausal Discovery

    Department of Technology, Management and Economics, Technical University of Denmark · Department of Mathematical Sciences,11 University of Copenhagen

  30. Mask2Cause: Causal Discovery via Adjacency Constrained Causal Attention

    May 8, 2026Omar Muhammad, Pasupuleti Dhruv Shivkant, Deepak N. SubramaniTime-Series Causal DiscoveryCausal Structure Learning

    1Indian Institute of Science, Bengaluru, India