{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:GDYO7NRHMX57OQUCCSKM54GEDJ","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":"2aa47d0666de3883d3ded62acb34a142afd622ccc15e9c3e872777dee1bec6fe","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-23T13:35:47Z","title_canon_sha256":"4026d3a805d6408ec5cc7943f3f6664f232fcb3a971ce009ae3d4b56909f6e24"},"schema_version":"1.0","source":{"id":"2606.24570","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.24570","created_at":"2026-06-24T01:15:34Z"},{"alias_kind":"arxiv_version","alias_value":"2606.24570v1","created_at":"2026-06-24T01:15:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.24570","created_at":"2026-06-24T01:15:34Z"},{"alias_kind":"pith_short_12","alias_value":"GDYO7NRHMX57","created_at":"2026-06-24T01:15:34Z"},{"alias_kind":"pith_short_16","alias_value":"GDYO7NRHMX57OQUC","created_at":"2026-06-24T01:15:34Z"},{"alias_kind":"pith_short_8","alias_value":"GDYO7NRH","created_at":"2026-06-24T01:15:34Z"}],"graph_snapshots":[{"event_id":"sha256:f3c0efb220f2f44344970f75a7e8d0506099baba6360c2f44515aa492fc9c0bb","target":"graph","created_at":"2026-06-24T01:15:34Z","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/2606.24570/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Vision-language contrastive pretraining has become the dominant recipe for 3D medical foundation models, leveraging the large volumes of paired scans and reports produced in clinical practice. However, medical images usually span dozens of organs, and radiological reports are much longer than typical natural image captions and are composed of multiple structured sections. CLIP-style pretraining compresses this structure by encoding each modality into a single global token, at the risk of losing important details. We introduce ConQuer (Concept Queries), an image-text pretraining method that aug","authors_text":"Amaury Prat, Antoine Saporta, Baptiste Callard, Charles Corbi\\`ere, Corentin Dancette, Julien Khlaut, Korentin Le Floch, Leo Butsanets, Leo Machado, Pierre Manceron, Th\\'eo Danielou, Tom Boeken","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-23T13:35:47Z","title":"Jolia: Concept-Level Vision-Language Alignment for 3D CT Contrastive Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.24570","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":"sha256:4748423fe967103a6367822633690ca45250685812a1b5712c7e81d9230935fa","target":"record","created_at":"2026-06-24T01:15:34Z","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":"2aa47d0666de3883d3ded62acb34a142afd622ccc15e9c3e872777dee1bec6fe","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-23T13:35:47Z","title_canon_sha256":"4026d3a805d6408ec5cc7943f3f6664f232fcb3a971ce009ae3d4b56909f6e24"},"schema_version":"1.0","source":{"id":"2606.24570","kind":"arxiv","version":1}},"canonical_sha256":"30f0efb62765fbf742821494cef0c41a526dd5f0d64e5c1fea4d9133934424fd","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"30f0efb62765fbf742821494cef0c41a526dd5f0d64e5c1fea4d9133934424fd","first_computed_at":"2026-06-24T01:15:34.214431Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-24T01:15:34.214431Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"NzR9uAFWCjko3dxX5RVqLSN5rC/4Z+hSmHki/mQr1me7uwWdK+H+MHsbqQ1EI/tSfHsoCW58YrPbGig0OyPqCg==","signature_status":"signed_v1","signed_at":"2026-06-24T01:15:34.214830Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.24570","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4748423fe967103a6367822633690ca45250685812a1b5712c7e81d9230935fa","sha256:f3c0efb220f2f44344970f75a7e8d0506099baba6360c2f44515aa492fc9c0bb"],"state_sha256":"b5a91eeb4f8ca787c622075460242aa4722a16d28950e492569e560bb52accce"}