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  "Title": "Pathwise Estimation of Covariate Balancing Propensity Scores",
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  "Description": "Provides pathwise estimation of regularized logistic\npropensity score models using covariate balancing loss\nfunctions rather than maximum likelihood. Regularization paths\nare fit via the 'adelie' elastic-net solver with a\n'glmnet'-like interface, yielding balancing weights that target\ncovariate balance for the ATE and ATT. Under lasso\npenalization, lambda bounds the maximum covariate imbalance, so\nthe regularization path traces a sequence of decreasing\nimbalance tolerances. For details, see Sverdrup & Hastie (2026)\n<doi:10.48550/arXiv.2602.18577>.",
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      "title": "Pathwise estimation of covariate balancing propensity scores.",
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