{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:PKBG4ENCY3ZHGNPYFIYD6LLFHN","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"3ec0ba7d4903001039f55f8daa12561451ca8bf67586720f17bb1d661898ce64","cross_cats_sorted":["econ.EM","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-05-18T18:35:20Z","title_canon_sha256":"af01db3e65221db59fc3ffebb0d5a3e2379226b111b134bb7bc440da9f22576b"},"schema_version":"1.0","source":{"id":"2605.19014","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.19014","created_at":"2026-05-20T01:04:42Z"},{"alias_kind":"arxiv_version","alias_value":"2605.19014v1","created_at":"2026-05-20T01:04:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.19014","created_at":"2026-05-20T01:04:42Z"},{"alias_kind":"pith_short_12","alias_value":"PKBG4ENCY3ZH","created_at":"2026-05-20T01:04:42Z"},{"alias_kind":"pith_short_16","alias_value":"PKBG4ENCY3ZHGNPY","created_at":"2026-05-20T01:04:42Z"},{"alias_kind":"pith_short_8","alias_value":"PKBG4ENC","created_at":"2026-05-20T01:04:42Z"}],"graph_snapshots":[{"event_id":"sha256:0f1d54acfd4269a00a31050d96386ea230133d602ed7c5a1168050a6a208fb1d","target":"graph","created_at":"2026-05-20T01:04:42Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2605.19014/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Microsimulation models used by ministries of finance and central banks rely on parametric processes for lifetime earnings that capture only first and second moments of the conditional distribution and miss long-range nonlinear structure. We propose SAGA, a decoder-only transformer for irregular tabular panel sequences, paired with a split conformal calibration wrapper that delivers individual-level prediction intervals with finite-sample marginal coverage guarantees. Trained on the longitudinal Swedish LISA register over 1990 to 2022, comprising 2,143,817 individuals and 61,284,903 person-year","authors_text":"Gustav Olaf Yunus Laitinen-Fredriksson Lundstr\\\"om-Imanov, Hafize Gonca C\\\"omert","cross_cats":["econ.EM","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-05-18T18:35:20Z","title":"SAGA: A Sequence-Adaptive Generative Architecture for Multi-Horizon Probabilistic Forecasting with Adaptive Temporal Conformal Prediction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.19014","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:531c7bd2a185fd130276a835bc34603312d81ce8a7ac98ff86b701ec680988fa","target":"record","created_at":"2026-05-20T01:04:42Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"3ec0ba7d4903001039f55f8daa12561451ca8bf67586720f17bb1d661898ce64","cross_cats_sorted":["econ.EM","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-05-18T18:35:20Z","title_canon_sha256":"af01db3e65221db59fc3ffebb0d5a3e2379226b111b134bb7bc440da9f22576b"},"schema_version":"1.0","source":{"id":"2605.19014","kind":"arxiv","version":1}},"canonical_sha256":"7a826e11a2c6f27335f82a303f2d653b4647db4a79f5359c00d403b8b2f955f6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7a826e11a2c6f27335f82a303f2d653b4647db4a79f5359c00d403b8b2f955f6","first_computed_at":"2026-05-20T01:04:42.502825Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T01:04:42.502825Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"i8BHpemBEbZfVhO391exWRHLTkSDVmuKxnKOS9D639UIWLfUu6QnkUstDLCIR1WpK4BmOFNfyt77VQpBL3VZCw==","signature_status":"signed_v1","signed_at":"2026-05-20T01:04:42.503726Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.19014","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:531c7bd2a185fd130276a835bc34603312d81ce8a7ac98ff86b701ec680988fa","sha256:0f1d54acfd4269a00a31050d96386ea230133d602ed7c5a1168050a6a208fb1d"],"state_sha256":"8e9c646f0e7e103d5fbc48bba7181f9dec6b0ea92618b2b622cf3710b039724a"}