{"schemaVersion":1,"target":{"type":"reading","id":"49b39caf399fe440de0b4c5696a6bf9862490d9a0d7c367a6be88ff4fa95a506","revision":"e92018db-e857-4908-8857-86f75697e270","revisionKind":"publication-id","title":"arXiv cs.AI: Polas reports conditional profit gains for TabPFN-3.5 over tuned GBDTs","url":"https://escapemeridian.com/readings/arxiv-cs-ai-polas-reports-conditional-profit-gains-for-tabpfn-3-49b39caf"},"source":{"type":"source","id":"https://arxiv.org/abs/2611.12942","revision":"b41b3c99b41439dde1243900962e2e4859372858f55ba1fd92c79d093909c8bf","revisionKind":"sha256-source-text","title":"Tabular Foundation Models vs Tuned Gradient Boosting for Telecom Churn: A Profit- and Calibration-Aware Evaluation","url":"https://arxiv.org/abs/2611.12942"},"status":"available","items":[],"next":null,"scope":"Explicit citations in public readings and public file attachments to this reading. Shared topics are not citations. Other artifact types need an explicit reference adapter."}