Causal

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Period ending 2026-09-21

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  1. Beyond the Illusion of Power: Calibrating Quasi-Experiments in Observational IS

    Sep 23, 2026Spandan Ghose ChowdhuryHeterogeneous Treatment Effects

  2. Multitask Regression with Pairwise Fusion

    Sep 23, 2026Xiaodong Li, Zhentao LiCovariate Shift

  3. Artificial intelligence surrogates for treatment effect estimation with before-and-after data

    Sep 23, 2026Frances Dean, Anna Neufeld, Joshua Barrios +2Heterogeneous Treatment EffectsSurrogate Performance

  4. Learning Risk Scores Robust to Unobserved Confounders

    Sep 22, 2026Ryan Edmonds, Yingxiao Ye, Sina Aghaei +3PropensityBiasing Score Estimation

  5. CVaR anchor regression protects against rare shifts

    Sep 22, 2026Malte LondschienCovariate ShiftDistribution Shifts

  6. Conditional Tensor Diffusion: Distributional Counterfactual Learning and Inference

    Sep 22, 2026Xinbing Kong, Zeyu Li, Junfan Mao +1Causal InferencesConditional Distribution

  7. Conformalized Quantile Regression and Minimax Limits of Fixed-Score Calibration under Known Covariate Shift

    Sep 21, 2026Rustam Isaev, Anton Conrad, Denis Belomestny +2Quantile RegressionCovariate Shift

  8. Circuit-Diff: Factual Edit-based Intervention Method for Localizing Knowledge in Attribution Graphs

    Sep 20, 2026Edward G. Friedman, Xiangchen SongCircuitsCausal Graph

  9. Decoupled Causal Discovery

    Sep 20, 2026Zhengkang Guan, Fei Wu, Kun KuangCausal Foundation ModelsFalse Discovery Rate

  10. ITSY: Causal Discovery From Irregular Time-Series Data

    Sep 20, 2026Wenbo Xu, Yue He, Yunhai Wang +2Causal Foundation ModelsTime Series

  11. Quantifying Overclaiming Propensity in Frontier LLM Agents

    Sep 17, 2026Nolan Smyth, Yorguin-Jose Mantilla-Ramos, Pascal Jr Tikeng Notsawo +6Coding AgentsPersonalized Large Language Model Agents

  12. Epidemiological Causal Graph Identification: Challenges, Identifiability and Algorithms

    Sep 17, 2026Sambit Mishra, Yingying Wang, Christine K. Johnson +1Causal Foundation ModelsStructural Equation Models

  13. MaSCoD: A Multi-Agent Framework for Structural-Context-Guided Candidate Causal Graph Generation

    Sep 17, 2026Yudai Nakada, Yuichiro Nishiura, Jin Michael SplichalCausal GraphReasoning Graphs

  14. Closed-World Resolution Against Tool Hallucination in LLM Agents

    Sep 16, 2026Laxmipriya Ganesh IyerLarge Language Model HallucinationTool Invocation

  15. Provable Guarantees and Efficient Learning of Structural Equation Models with Latent Confounders

    Sep 16, 2026Weijian Yu, Jean HonorioStructural Equation ModelsLatent Confounders

  16. CSWAM: Better Causal Semantic Representations for Out-of-Distribution Generalization in World Action Models

    Sep 16, 2026Tianbin Liu, Jian Zhu, Taiyi Su +5Efficient World-Action ModelFaster-Wam

  17. Faithful yet Collusive: Why Chain-of-Thought Monitoring Cannot Detect Collusion in LLM Pricing Agents under Oligopolistic Competition

    Sep 16, 2026Dohun Lee, Hyunwoo ParkAlgorithmic CollusionPrices

  18. Decodability is Not Causality: Dissociating Probe Readouts from Behavioral Drivers via SAE Decomposition

    Sep 16, 2026Devesh Tiwari, Camille Davis, Shivank Sinha +3Model ActivationsCausal Reasoning

  19. Regional Explanations via Causal Sufficiency and Necessity

    Sep 16, 2026Xuexin Chen, Peng Liang, Zijian Li +2ExplainabilitySufficient Conditions

  20. Causal-History Test-Time Scaling for Failure Recovery in Autoregressive World-Action Models

    Sep 16, 2026Lin Li, Long Chen, Kwunhang +10Efficient World-Action ModelAutoregressive Model

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

    Sep 16, 2026Sambit Mishra, Urbashi MitraStructural Equation ModelsIdentifiability

  22. Who Judges Matters: Measuring Family-Conditioned Preference in LLM-as-Judge Panels

    Sep 15, 2026David Ababio Awuni, Luke E. K. Achenie, Benjamin Tei Partey +2JudgesLlm-As-A-Judge

  23. Information Set Emulation: Causal Certificates for AI Derived EHR Features

    Sep 15, 2026Takes Fujita, Nobutaka HattoriElectronic Health RecordsCausal Reasoning

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

    Sep 15, 2026Takes Fujita, Nobutaka HattoriCausal InferencesCovariate Shift

  25. TIO-Former: Ultra-Lightweight 6-Directional ToF-Inertial Odometry for Nano-UAVs via a Streaming Causal Transformer

    Sep 15, 2026Yang Liu, Yifan He, Wenhao Zhao +9Inertial OdometryAutonomous Drone Navigation

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

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

  27. Causal Discovery via Transformed Low-Rank Quantile Surfaces

    Sep 15, 2026Ryo Kamimura, Thong PhamQuantile RegressionStructural Causal Model

  28. Copula Adapted Directed Acyclic Graph for Cluster Representation of Biomedical Data

    Sep 14, 2026Heranga K. Rathnasekara, Norou Diawara, Manar D. SamadCausal Foundation ModelsK-Means

  29. A Chosen Future Can Still Be Rewritten: Causal Writability in Video Models

    Sep 14, 2026Xingyun Wang, Haomin Zheng, Man Yuan +2Causal Reasoning

  30. MoveBench: A Benchmark for Global-Scale Wildlife Movement Forecasting

    Sep 14, 2026Justin Kay, Shir Bar, Ellen O. Aikens +28Trajectory PredictionCovariate Shift

  31. Transfer Learning for Socioeconomic Estimation in Forced-Displacement Settings

    Sep 14, 2026Steven Ndung'u, Adel Daoud, Ismael Yacoubou Djima +2Humanitarian ReportsSri Lanka

  32. Big Brains and Changing Environments: Cause or Consequence?

    Sep 14, 2026Sian Heesom-Green, Jonathan Shock, Geoff NitschkeEvolutionAlphaevolve

  33. When Correlations Mislead: Confounder-Aware Multi-View Urban Region Representation Learning

    Sep 14, 2026Sean Bin Yang, Ying Sun, Zongyi Xu +6Multi-ViewCross-View

  34. Conformal Individual Treatment Effect Estimation under Networked Interference

    Sep 14, 2026Matteo Zecchin, Osvaldo SimeoneHeterogeneous Treatment EffectsConformal Prediction

  35. Membership Inference via Pairwise Likelihood Ratios

    Sep 14, 2026Shengjie Niu, Zebin Yun, Yeheng Ge +1Membership Inference AttacksMembership Inference

  36. Pixel Decodability Is Not a Compression Signal: Causally Evaluating Importance Proxies for Visual KV-Cache Eviction

    Sep 14, 2026Chenyu Zhou, Qiliang Jiang, Shuning Wu +1Key-Value CachePixels

  37. MedSNIP: Building and Benchmarking Snippet-Level Granularity for Medical Fact Verification

    Sep 14, 2026Hasan Iqbal, Sarfraz Ahmad, Hyunjae Kim +5FactsDiagnostic Benchmark

  38. Context-Aware Causal Gaze Forecasting for Human-Vehicle Interaction During In-Cabin Tracking Dropouts

    Sep 14, 2026Shabnam Shabani, Ghazal FarhaniGaze Target EstimationGaze

  39. Cross-Block Conditioning in Deep Boltzmann Machines for Statistical Data Fusion

    Sep 14, 2026Junichiro NiimiTemporal Fusion TransformerCovariate Shift

  40. General Quantification of Covariate and Concept Shifts

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

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

    Sep 12, 2026Hyojung HanLarge Language Model ResponsesQwen3

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

    Sep 12, 2026Masahiro Kato, Daiki Honma, Taka KatoGenerativeCausal Inferences

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

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

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

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

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

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

  46. Efficient Fairness Auditing Across Guidance Scales in Text-to-Image Diffusion Models via Causal Abstraction

    Sep 8, 2026Nabila Tasfiha Rahman, Rajatsubhra Chakraborty, Depeng Xu +1Fairness AuditsText-To-Image Diffusion Models

  47. Tensor Network Moral Graph Recovery of Discrete Probability Distributions

    Sep 8, 2026Á. Troyano Olivas, Chi-Hang Fred Fung, Hans H. Brunner +2Causal GraphTensor Networks

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

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

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

    Sep 8, 2026Sixtine SphabmixayEstimatorsCovariate Shift

  50. Not All Variables Agree: Reliability-Aware Variable-Wise Gradient Surgery for Multivariate Time-Series Forecasting

    Sep 8, 2026Jinwoo Park, Hyeongwon Kang, Pilsung KangMultivariate Time Series ForecastingMultivariate Forecasting

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

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

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

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

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

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

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

    Sep 7, 2026Alexander DoudkinPopulationsPropensity

  55. A Computationally Feasible Framework for Causal Probabilistic Explanation

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

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

    Sep 3, 2026Yakov Pyotr ShkolnikovDeceptionLarge Language Model Decision-Making

  57. Hardware-Aware FP4 FlashAttention-4

    Sep 3, 2026Robert HuQuadratic AttentionTensor Programs

  58. 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

  59. Federated Causal Discovery via Regression-Directed Cumulants

    Sep 3, 2026Pablo Torrijos, Fabio Stella, José A. Gámez +1Causal Foundation ModelsFederated Learning

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

    Sep 3, 2026Martin Rabel, Jakob RungeCausal ReasoningIdentifiability