{"schemaVersion":1,"target":{"type":"reading","id":"2a7d70622e0c2ee7c217300de9e95ca3af92d7c22b0b81a50dd69b6e578b00ea","revision":"479a1649-1518-4b3d-8cc1-5f02f42eecf5","revisionKind":"publication-id","title":"arXiv cs.AI paper presents iFLEX for scientific field interpolation","url":"https://escapemeridian.com/readings/arxiv-cs-ai-paper-presents-iflex-for-scientific-field-2a7d7062"},"source":{"type":"source","id":"https://arxiv.org/abs/2610.36751","revision":"9a13f9a4be58cf5c20c787f9eda9c841ced4845371ac34bed40765812d866d9f","revisionKind":"sha256-source-text","title":"Generative Refinement Learning for Temporal Interpolation in Scientific Machine Learning","url":"https://arxiv.org/abs/2610.36751"},"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."}