{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:Y4YNYYLEV6W7XWUUHXIKR5PEFU","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":"7965e36e654c37bf47f8ae90344533c2c21306e59015daf07047098d333b59dc","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-17T18:01:18Z","title_canon_sha256":"5fd18c2a515aa7f57912872d089ff44a31689d6f5bec8bef05a353e8c91d0c1b"},"schema_version":"1.0","source":{"id":"2606.19460","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.19460","created_at":"2026-06-19T16:12:26Z"},{"alias_kind":"arxiv_version","alias_value":"2606.19460v1","created_at":"2026-06-19T16:12:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.19460","created_at":"2026-06-19T16:12:26Z"},{"alias_kind":"pith_short_12","alias_value":"Y4YNYYLEV6W7","created_at":"2026-06-19T16:12:26Z"},{"alias_kind":"pith_short_16","alias_value":"Y4YNYYLEV6W7XWUU","created_at":"2026-06-19T16:12:26Z"},{"alias_kind":"pith_short_8","alias_value":"Y4YNYYLE","created_at":"2026-06-19T16:12:26Z"}],"graph_snapshots":[{"event_id":"sha256:145344f184028e92df73e67699d89856fa10f7d913c46caba3278e286500cea6","target":"graph","created_at":"2026-06-19T16:12:26Z","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/2606.19460/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We introduce the first generative foundation model for chest radiograph synthesis trained from scratch at the billion-parameter scale. Existing radiographic AI models often suffer from poor generalisation across patient subpopulations, institutions, and acquisition settings, resulting in limited real-world clinical utility. Controlled, high-fidelity synthesis of chest radiographs is a promising path toward diversifying clinical datasets and evaluating the robustness of diagnostic models. Therefore, we present the largest specialist generative foundation model for chest radiographs to date, wit","authors_text":"Ben Glocker, Charles Jones, Christopher V. Cosgriff, Dominic C. Marshall, Emma A.M. Stanley, Fabio De Sousa Ribeiro, Laurent Renard Trich\\'e, Panagiotis Dimitrakopoulos, Sotirios A. Tsaftaris, Tian Xia","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-17T18:01:18Z","title":"Scaling Generative Foundation Models for Chest Radiography with Rectified Flow Transformers"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.19460","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":"sha256:5d631da6e84f02cb996141d880962dcfbcc850f8242c8eccfa8573b1fe1630e1","target":"record","created_at":"2026-06-19T16:12:26Z","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":"7965e36e654c37bf47f8ae90344533c2c21306e59015daf07047098d333b59dc","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-06-17T18:01:18Z","title_canon_sha256":"5fd18c2a515aa7f57912872d089ff44a31689d6f5bec8bef05a353e8c91d0c1b"},"schema_version":"1.0","source":{"id":"2606.19460","kind":"arxiv","version":1}},"canonical_sha256":"c730dc6164afadfbda943dd0a8f5e42d1486f2dd2e184e7e0f890487444edb33","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c730dc6164afadfbda943dd0a8f5e42d1486f2dd2e184e7e0f890487444edb33","first_computed_at":"2026-06-19T16:12:26.384480Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-19T16:12:26.384480Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"hyfJf5EFL13Pv7Qh0R0NWDxPfNpwNReyAeI64tKIMy7Np2zzcDuJ6Dc9sW0D29KwtJaVMi7lLcW/an4mI5RzBw==","signature_status":"signed_v1","signed_at":"2026-06-19T16:12:26.384893Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.19460","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5d631da6e84f02cb996141d880962dcfbcc850f8242c8eccfa8573b1fe1630e1","sha256:145344f184028e92df73e67699d89856fa10f7d913c46caba3278e286500cea6"],"state_sha256":"d73655676c39d839a64299e2708aaf04ceb87c32c892425aba1e617867973eac"}