Causal Discovery

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Period ending 2026-09-14

15 new papers

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Period ending 2026-09-07

19 new papers

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  1. Regional Explanations via Causal Sufficiency and Necessity

    Sep 16, 2026Xuexin Chen, Peng Liang, Zijian Li +2Structural Causal Model

  2. On the Identifiability of Mixed Ordinal and Exponential Family Causal DAGs under Linear Parametric Models

    Sep 16, 2026Sambit Mishra, Urbashi MitraIdentifiabilityStructural Equation Modeling

  3. When AI Generates Covariates: Causal Typing and Estimand Drift in Sequential Experiments

    Sep 15, 2026Takes Fujita, Nobutaka HattoriCovariate ShiftControlled Study

  4. Splitting the Difference: Interpretable Causal Forests for Treatment Effect Heterogeneity and Bias

    Sep 15, 2026Nicolas Alexander Ihlo, Merle BehrHeterogeneous Treatment EffectsRandom Forest

  5. Conformal Individual Treatment Effect Estimation under Networked Interference

    Sep 14, 2026Matteo Zecchin, Osvaldo SimeoneHeterogeneous Treatment Effects

  6. Cloud Workflow Scheduling Based on Graph Attention-Driven Hierarchical Reinforcement Learning

    Sep 14, 2026Zongjin Li, Shaohan Feng, Chunxi Yang +1Multi-View Gated Graph Attention NetworkDirected Acyclic Graph

  7. Generative Marketing Mix Modeling: A Causal Inference Framework Linking GEO and GEM to Business Impact

    Sep 12, 2026Masahiro Kato, Daiki Honma, Taka KatoGenerativeBrand Pairs

  8. Off-Target Effects of Response-Style Alignment in a Korean 27B Language Model

    Sep 12, 2026Hyojung HanLarge Language Model ResponsesKorean

  9. General Quantification of Covariate and Concept Shifts

    Sep 12, 2026Hongbo Chen, Li Charlie XiaDistribution ShiftsCovariate Shift

  10. Polyhedral Geometry of Time-to-First-Spike Neural Networks

    Sep 11, 2026Manjot Singh, Guido Montúfar, Gitta KutyniokSpiking Neural NetworksBinary Spikes

  11. CausalArena: Benchmarking Causal Discovery in the Foundation Model Era

    Sep 10, 2026Zi-Rong Li, Si-Yang Liu, Tian-Zuo Wang +1Causal DiscoveryStructural Causal Model

  12. Differentially Private Average Treatment Effect Estimation by Propensity Score Blocking

    Sep 8, 2026Duncan Stewardson, Grayson W. White, Adam GroceHeterogeneous Treatment EffectsPropensity

  13. Tensor Network Moral Graph Recovery of Discrete Probability Distributions

    Sep 8, 2026Á. Troyano Olivas, Chi-Hang Fred Fung, Hans H. Brunner +2Causal GraphDirected Acyclic Graph

  14. CausalChapter: Improving Long-Video Chaptering with Interventional Dependency Modeling

    Sep 8, 2026Xinran Duan, Guozhang Li, Yaoyao Zhong +3Video UnderstandingVideo Captioning

  15. Optimal estimation for Functional Linear Regression with Noisy Discretized Data

    Sep 8, 2026Sixtine SphabmixayRegressionEstimators

  16. Target-Independent Micro-Interventions for Predicting Training Response Across Language-Model Families

    Sep 8, 2026Zhongxuan Liu, Sicheng Zhou, Hongzhi WangReadoutCausal Intervention

  17. Semi-Supervised Learning under Spatially Biased Sampling

    Sep 7, 2026Bright Wiredu Nuakoh, Francky Fouedjio, Stephen Bradshaw +4Semi-Supervised LearningBridging Geographic Bias

  18. CausalVerify: An Execution-Grounded Benchmark for LLM Causal Inference Workflows

    Sep 7, 2026Yonghong Zhang, Ricardo Correia, Isabel M. Parra +1Causal InferencesCorrectness

  19. ReactVAU: A Slow-Fast Decoupled Framework for Streaming Video Anomaly Understanding

    Sep 7, 2026Chia-Hui Chen, Shih-Ying Yeh, Fu-En Yang +2Video Anomaly DetectionStreaming Video

  20. InfluenceField: A Differentiable Field with Interventionally Identifiable Causal Structure for Multimodal World Modeling

    Sep 7, 2026Zihao Yang, Zijia Wang, Zhiqiu HuangCausal InterventionInfluence

  21. Marginal Fidelity Does Not Establish User Simulation in Demographic Synthetic Survey Panels: Response Contracts, Support Collapse and Conditioning Failure

    Sep 7, 2026Alexander DoudkinPopulationsObservational Data

  22. A Computationally Feasible Framework for Causal Probabilistic Explanation

    Sep 3, 2026Rafal Urbaniak, Sam Witty, Daniel Waxman +7Structural Causal ModelCausal Structure and Reasoning

  23. From Deceptive Outputs to Deceptive Mechanisms: A Causal Framework for Language-Model Deception Research

    Sep 3, 2026Yakov Pyotr ShkolnikovDeceptionCognitive Biases

  24. A location-invariant estimator of extremal quantile treatment effects for heavy-tailed distributions

    Sep 3, 2026Xin Yu, Shuwei Huang, Jicheng Liu +4Heterogeneous Treatment EffectsQuantile Regression

  25. CauseCollab: Causal Unified and Modality-Agnostic Network for Heterogeneous Collaborative Perception

    Sep 3, 2026Weize Li, Yang Li, Quan Yuan +3Collaborative PerceptionCollaboration

  26. Federated Causal Discovery via Regression-Directed Cumulants

    Sep 3, 2026Pablo Torrijos, Fabio Stella, José A. Gámez +1Causal DiscoveryTour

  27. Symmetries and Causality: Causal Effect Identification Beyond IID Data

    Sep 3, 2026Martin Rabel, Jakob RungeStructural Causal ModelCausal Structure and Reasoning

  28. Guide, Not Bind: Why Defeasible Priors Fail in Augmented Lagrangian Causal Discovery

    Sep 3, 2026Sairam Sundararaman, Sara Girdhar, Manit Narasimha Murthy +2Causal DiscoveryPriors

  29. It's the Problem, Not the Path: Budget and Difficulty Confounds in LLM Reasoning Trajectories

    Sep 3, 2026Yigit Utku BulutLLM Reasoning MethodsReasoning Traces

  30. Portable Causal Fairness Across Synthetic Data Generator Families

    Sep 2, 2026Steven Golob, Sikha Pentyala, Martine De CockFairness-Aware LearningSynthetic Data

  31. ObserverBench: Testing Mechanistic Estimates for Intervention and Control

    Sep 2, 2026Vijay ErramilliMechanistic InterpretabilityCausal Intervention

  32. Causal Foundation Models

    Sep 2, 2026Christopher Stith, Hossein Rahmani, Jesse C. CresswellCausal InferencesCausal Discovery

  33. Who Drives the Probability Game of VLMs? A Temporal Causal Drive Evaluation Framework

    Sep 2, 2026Shuyao Xiao, Shengling Wang, Haoyu Niu +4Multimodal GenerationCausal Structure and Reasoning

  34. The Structure of Quantization Damage in LLMs: Why the Next Bit Should Be Spent Globally

    Sep 1, 2026Jundong Hu, Shekar RamachandranQuantizationBudgets

  35. EvoSCM: Scientific Belief Revision Through Causal Model Evolution and Experimentation

    Sep 1, 2026Qing Zhao, Haowei Li, Weijian Deng +2Scientific DiscoveryScientific Agents

  36. Exploring Sparse Autoencoders in Text-Based Causal Confounding Adjustment

    Sep 1, 2026Mian Zhong, Katherine A. Keith, Anjalie FieldLatent ConfoundersCausal Inferences

  37. Some Emotions Run Deeper: Layer-wise Probing and Causal Intervention in Large Language Models

    Sep 1, 2026Tian Fang, Gaël Guibon, Davide BuscaldiEmotionCorpus

  38. Replicating TRACE: A Practitioner's Guide to Its Threshold and Particle Budget

    Sep 1, 2026Alex Chadyuk, Alicia Zhang, Roy KucukatesCausal GraphTraces

  39. Embedded Conditional Independence Tests for Large Language Model Generated Text with an Application to German Parliament Speeches

    Sep 1, 2026Marco Simnacher, Georg Keilbar, Benjamin König +2Conditional IndependenceLarge Language Model Generation

  40. Verifiable Disaster Storylines and Causal Knowledge Graphs: A Citation-Grounded Pipeline from Heterogeneous Humanitarian Sources

    Sep 1, 2026Ivan Decostanzi, Michele Ronco, Sergio Consoli +8DisastersCausal Graph

  41. Confounding Masquerading as Improvement: A Systematic Evaluation of Offline Reinforcement Learning for Stroke Antithrombotic Treatment in a 129,000-Patient Registry

    Aug 31, 2026Kihun RheeOffline Safe Reinforcement LearningStroke

  42. Generating Workflow DAGs from Natural Language with Non-Reasoning LLMs

    Aug 31, 2026Anand Iyer, Bhanu Khetharpal, Srinivas Upadhya +1Reasoning GraphsDirected Acyclic Graph

  43. When Prediction Error Is Not Enough: Evaluating Nuisance-Function Prediction for Causal Estimation

    Aug 30, 2026Cong CaoCausal InferencesCalibrated Predictors

  44. The Intervention Gap in Latent World Models

    Aug 30, 2026Donna VakalisLatent World ModelsCausal Intervention

  45. Neural ODE enhanced linear mixed effect models for estimating complex association patterns of time-varying covariates with the marker trajectory

    Aug 30, 2026Zhe Aurore Li, Quentin Clairon, Cécilia Samieri +3Generalized Linear ModelNeural Ordinary Differential Equations

  46. Actionable CBFI: Integrating Structural Decomposition and Causal Counterfactual Recourse for Tabular Machine Learning

    Aug 28, 2026Sejong OhStructural Causal ModelXai

  47. Random Hazard Forests

    Aug 21, 2026Hemant Ishwaran, Eileen M. Hsich, Udaya B. Kogalur +1Time-To-Event DataRandom Forest

  48. Debiased Inference for AI-Generated Data without Gold-Standard Labels: Identification via Multiple Imperfect Measurements

    Aug 18, 2026Naoki Egami, Sooahn ShinCausal InferencesConditional Independence

  49. Context-Matched Distillation: Teacher Causality for Autoregressive Video Distillation

    Aug 13, 2026Hmrishav Bandyopadhyay, Xuanchi Ren, Zijian Huang +7Autoregressive Video GenerationVideo Diffusion Models

  50. Foundations of Independent Component Analysis

    Aug 13, 2026Patrick ForréIndependent Component AnalysisIdentifiability

  51. Discovering Efficient and Explainable Communication Topologies for LLM-based Multi-Agent Systems via Causal Inference

    Aug 13, 2026Junzhi Li, Peng He, Qirui Ji +3Communication TopologiesInformation-Flow Control

  52. Agent Behavioral Contracts II: Certifying Compositional Reliability Without Assuming Independence

    Aug 13, 2026Varun Pratap Bhardwaj, Garima Singh, Arun Pratap BhardwajReliabilityStep-Level Failure Attribution

  53. Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value

    Aug 13, 2026Akihito SudoValue FunctionsValue

  54. PatientAct: Theory-Grounded Mental Health Client Simulation

    Aug 13, 2026Sahand Sabour, TszYam NG, Yaqian Chen +3Simulated PatientsSocial Simulations

  55. General Probabilities of Causation with Causal Knowledge

    Aug 12, 2026Xin Shu, Zhen Lei, Ang LiStructural Causal ModelCausal Structure and Reasoning

  56. Interpretable Causal Discovery via Causal-Effect Constraints

    Aug 12, 2026Cixuan Zhang, Guy Van den Broeck, Benjie WangCausal DiscoveryCausal Graph

  57. CAS: A Causal Attribution Score for Local and Global Explainable Artificial Intelligence

    Aug 12, 2026Michael Georgiades, Charalambia VarnavaShapley ValueExplainable Artificial Intelligence

  58. When Can You Trust Offline Evaluation of Equal-Cost Top-k Allocation? A Controlled, Reproducible Benchmark and Practitioner's Guide

    Aug 12, 2026Binshuang LiPropensityEstimators

  59. Learning Under Treatment-Induced Label Indeterminacy with Expert Annotations of Counterfactual Outcomes: A Case Study in Neurological Prognostication

    Aug 12, 2026Xiaobin Shen, Chloe Y. H. Huang, Jonathan Elmer +1PrognosticsClinical Prediction

  60. Causal inference for group-contaminated structured outcomes: observable quotients, lossless reduction and exact randomization inference

    Aug 12, 2026Usef Faghihi, Amir SakiCausal InferencesControlled Study