{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:HYE7TXP3HAZZLRR5HHIT4PIH7G","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":"57545df267ebb25253f6005efa320e0b2c9283cd68d2faa62827150c9c4c4662","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-03-06T16:51:42Z","title_canon_sha256":"ffacf92721099f780040dc5633570d1b6d0620d8d5011d614e6cd666cd52ab0a"},"schema_version":"1.0","source":{"id":"2603.06467","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2603.06467","created_at":"2026-06-23T02:13:22Z"},{"alias_kind":"arxiv_version","alias_value":"2603.06467v2","created_at":"2026-06-23T02:13:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2603.06467","created_at":"2026-06-23T02:13:22Z"},{"alias_kind":"pith_short_12","alias_value":"HYE7TXP3HAZZ","created_at":"2026-06-23T02:13:22Z"},{"alias_kind":"pith_short_16","alias_value":"HYE7TXP3HAZZLRR5","created_at":"2026-06-23T02:13:22Z"},{"alias_kind":"pith_short_8","alias_value":"HYE7TXP3","created_at":"2026-06-23T02:13:22Z"}],"graph_snapshots":[{"event_id":"sha256:9eb8ec38f8c9a8f77dd5fc4149ae9c42c0e7ff62c500e4fb56b4dcd1b9588b9a","target":"graph","created_at":"2026-06-23T02:13:22Z","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/2603.06467/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Radiology foundation models (RFMs) have largely inherited the scale-first recipe of natural-image vision--language pre-training. This recipe is difficult to deploy in 3D radiology, where training corpora are smaller, reports vary across institutions, and receiving hospitals often need local adaptation under privacy and compute constraints. We ask whether routine radiology reports can instead be converted into auditable diagnostic supervision that shapes the image encoder, text encoder, aligned space, and local-adaptation procedure. We develop GreenRFM, a supervision-centric pre-training framew","authors_text":"Haoran Lai, Hongchun Zhang, Mingyue Zhao, Qiuli Wang, Rongsheng Wang, Rui Zhou, Rundong Wang, Shaohua Kevin Zhou, Shuai Ming, Wei Chen, Wei Wei, Xiaodong Tao, Yingtai Li, Yuhe Tian, Yujia Li, Zhiyang He","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-03-06T16:51:42Z","title":"GreenRFM: Learning a resource-efficient radiology vision-language foundation model via supervision-centric pre-training"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2603.06467","kind":"arxiv","version":2},"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":"sha256:2794cba90ed06989256410972d4daecb73c29d7b03b900a13015519caa8b80eb","target":"record","created_at":"2026-06-23T02:13:22Z","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":"57545df267ebb25253f6005efa320e0b2c9283cd68d2faa62827150c9c4c4662","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-03-06T16:51:42Z","title_canon_sha256":"ffacf92721099f780040dc5633570d1b6d0620d8d5011d614e6cd666cd52ab0a"},"schema_version":"1.0","source":{"id":"2603.06467","kind":"arxiv","version":2}},"canonical_sha256":"3e09f9ddfb383395c63d39d13e3d07f9855acd3b2516b483619fc86cb8003f74","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3e09f9ddfb383395c63d39d13e3d07f9855acd3b2516b483619fc86cb8003f74","first_computed_at":"2026-06-23T02:13:22.039760Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-23T02:13:22.039760Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"CEu9NO92cLTMewuKMQBY+CT/jyCFx1awxrcgDTccXIjwANFIS5T+cVQbzrcTMBmsuFhFrxhLibzZxah8g5YoCw==","signature_status":"signed_v1","signed_at":"2026-06-23T02:13:22.040189Z","signed_message":"canonical_sha256_bytes"},"source_id":"2603.06467","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2794cba90ed06989256410972d4daecb73c29d7b03b900a13015519caa8b80eb","sha256:9eb8ec38f8c9a8f77dd5fc4149ae9c42c0e7ff62c500e4fb56b4dcd1b9588b9a"],"state_sha256":"44c18a6fba637573db8d4c0f2ccc6c9a9382826a3732f2d101d789428813a432"}