Jianfei Cao, Michael P. Leung: Neighborhood Stability in Double/Debiased Machine Learning with Dependent Data https://arxiv.org/abs/2511.10995 https://arxiv.org/pdf/2511.10995 https://arxiv.org/html/2511.10995

Vincent Starck: Improving control over unobservables with network data https://arxiv.org/abs/2511.00612 https://arxiv.org/pdf/2511.00612 https://arxiv.org/html/2511.00612

Mengchu Zheng, Matteo Bonvini, Zijian Guo: Perturbed Double Machine Learning: Nonstandard Inference Beyond the Parametric Length https://arxiv.org/abs/2511.01222 https://arxiv.org/pdf/2511.01222 https://arxiv.org/html/2511.01222

Xiaohong Chen, Zhenxiao Chen, Wayne Yuan Gao: Inference on Welfare and Value Functionals under Optimal Treatment Assignment https://arxiv.org/abs/2510.25607 https://arxiv.org/pdf/2510.25607 https://arxiv.org/html/2510.25607

Xiaohong Chen, Haitian Xie: Local Overidentification and Efficiency Gains in Modern Causal Inference and Data Combination https://arxiv.org/abs/2510.16683 https://arxiv.org/pdf/2510.16683 https://arxiv.org/html/2510.16683

Pawel Morzywolek, Peter B. Gilbert, Alex Luedtke: Inference on Local Variable Importance Measures for Heterogeneous Treatment Effects https://arxiv.org/abs/2510.18843 https://arxiv.org/pdf/2510.18843 https://arxiv.org/html/2510.18843

Francis J. DiTraglia, Laura Liu: Bayesian Double Machine Learning for Causal Inference https://arxiv.org/abs/2508.12688 https://arxiv.org/pdf/2508.12688 https://arxiv.org/html/2508.12688

Victor Chernozhukov, Iv\'an Fern\'andez-Val, Jonas Meier, Aico van Vuuren, Francis Vella: Bivariate Distribution Regression; Theory, Estimation and an Application to Intergenerational Mobility https://arxiv.org/abs/2508.12716 https://arxiv.org/pdf/2508.12716 https://arxiv.org/html/2508.12716

Kevin Dano, Bo E. Honor\'e, Martin Weidner: Binary choice logit models with general fixed effects for panel and network data https://arxiv.org/abs/2508.11556 https://arxiv.org/pdf/2508.11556 https://arxiv.org/html/2508.11556

Diego Vallarino: Adaptive Market Intelligence: A Mixture of Experts Framework for Volatility-Sensitive Stock Forecasting https://arxiv.org/abs/2508.02686 https://arxiv.org/pdf/2508.02686 https://arxiv.org/html/2508.02686

Facundo Arga\~naraz, Juan Carlos Escanciano: Debiased Machine Learning for Unobserved Heterogeneity: High-Dimensional Panels and Measurement Error Models https://arxiv.org/abs/2507.13788 https://arxiv.org/pdf/2507.13788 https://arxiv.org/html/2507.13788