{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:6XC7I6KLPRZ42UMSFYT73ZLZB7","short_pith_number":"pith:6XC7I6KL","schema_version":"1.0","canonical_sha256":"f5c5f4794b7c73cd51922e27fde5790fff77200a74dead980c06ed2f3e331681","source":{"kind":"arxiv","id":"2605.24371","version":1},"attestation_state":"computed","paper":{"title":"SliceWorld: A Predictive and Controllable World-State Model for CT Report Generation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.CV","authors_text":"Yan Song, Yuanhe Tian","submitted_at":"2026-05-23T03:18:56Z","abstract_excerpt":"CT report generation (CTRG) requires models to summarize three-dimensional anatomical context and pathological findings from hundreds of axial slices. Existing methods typically learn a direct image-to-text mapping, providing limited mechanisms for modeling how CT evidence evolves across slices or how reports respond to controlled changes in latent lesion-related factors. We propose SliceWorld, a CT-specific world-state framework that treats an axial CT scan as an ordered sequence along the z-axis. SliceWorld encodes prefix CT evidence into factor-aware latent states containing anatomy, lesion"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2605.24371","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-05-23T03:18:56Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"2a4b1d035e7d309b7feecfe8dd3eb98df9c3bf7ccb6c75b65a5bad10b5449b02","abstract_canon_sha256":"2cb8cb244294f1758df940185fe1e63012e9d36a3f88be4ef868eaf2205f5be6"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-26T01:03:02.329388Z","signature_b64":"Sq9V7TvTzxqq3XhKvsPxpXsWeaz4cPje/2+quYOjekSmVkgN+7BQDbyvBFq4BB0/Pnytt3Yy+0KRta1773kADg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f5c5f4794b7c73cd51922e27fde5790fff77200a74dead980c06ed2f3e331681","last_reissued_at":"2026-05-26T01:03:02.328583Z","signature_status":"signed_v1","first_computed_at":"2026-05-26T01:03:02.328583Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"SliceWorld: A Predictive and Controllable World-State Model for CT Report Generation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.CV","authors_text":"Yan Song, Yuanhe Tian","submitted_at":"2026-05-23T03:18:56Z","abstract_excerpt":"CT report generation (CTRG) requires models to summarize three-dimensional anatomical context and pathological findings from hundreds of axial slices. Existing methods typically learn a direct image-to-text mapping, providing limited mechanisms for modeling how CT evidence evolves across slices or how reports respond to controlled changes in latent lesion-related factors. We propose SliceWorld, a CT-specific world-state framework that treats an axial CT scan as an ordered sequence along the z-axis. SliceWorld encodes prefix CT evidence into factor-aware latent states containing anatomy, lesion"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.24371","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2605.24371/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2605.24371","created_at":"2026-05-26T01:03:02.328706+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.24371v1","created_at":"2026-05-26T01:03:02.328706+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.24371","created_at":"2026-05-26T01:03:02.328706+00:00"},{"alias_kind":"pith_short_12","alias_value":"6XC7I6KLPRZ4","created_at":"2026-05-26T01:03:02.328706+00:00"},{"alias_kind":"pith_short_16","alias_value":"6XC7I6KLPRZ42UMS","created_at":"2026-05-26T01:03:02.328706+00:00"},{"alias_kind":"pith_short_8","alias_value":"6XC7I6KL","created_at":"2026-05-26T01:03:02.328706+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/6XC7I6KLPRZ42UMSFYT73ZLZB7","json":"https://pith.science/pith/6XC7I6KLPRZ42UMSFYT73ZLZB7.json","graph_json":"https://pith.science/api/pith-number/6XC7I6KLPRZ42UMSFYT73ZLZB7/graph.json","events_json":"https://pith.science/api/pith-number/6XC7I6KLPRZ42UMSFYT73ZLZB7/events.json","paper":"https://pith.science/paper/6XC7I6KL"},"agent_actions":{"view_html":"https://pith.science/pith/6XC7I6KLPRZ42UMSFYT73ZLZB7","download_json":"https://pith.science/pith/6XC7I6KLPRZ42UMSFYT73ZLZB7.json","view_paper":"https://pith.science/paper/6XC7I6KL","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.24371&json=true","fetch_graph":"https://pith.science/api/pith-number/6XC7I6KLPRZ42UMSFYT73ZLZB7/graph.json","fetch_events":"https://pith.science/api/pith-number/6XC7I6KLPRZ42UMSFYT73ZLZB7/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/6XC7I6KLPRZ42UMSFYT73ZLZB7/action/timestamp_anchor","attest_storage":"https://pith.science/pith/6XC7I6KLPRZ42UMSFYT73ZLZB7/action/storage_attestation","attest_author":"https://pith.science/pith/6XC7I6KLPRZ42UMSFYT73ZLZB7/action/author_attestation","sign_citation":"https://pith.science/pith/6XC7I6KLPRZ42UMSFYT73ZLZB7/action/citation_signature","submit_replication":"https://pith.science/pith/6XC7I6KLPRZ42UMSFYT73ZLZB7/action/replication_record"}},"created_at":"2026-05-26T01:03:02.328706+00:00","updated_at":"2026-05-26T01:03:02.328706+00:00"}