{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:3DZCRDPNTHVOE6E4D3TEEJPGHC","short_pith_number":"pith:3DZCRDPN","canonical_record":{"source":{"id":"2606.20112","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-18T11:35:11Z","cross_cats_sorted":["eess.IV"],"title_canon_sha256":"8d295a4794f860c1da03c12607eb090d0ad1ec82cf56fcb15e4dfc722ec866c8","abstract_canon_sha256":"ad8974b3e77316cd9b0a4d04bd18eedea69b3140417c9db26646d90e980701ff"},"schema_version":"1.0"},"canonical_sha256":"d8f2288ded99eae2789c1ee64225e638acfae50b571412e4bfe53f93063d43f2","source":{"kind":"arxiv","id":"2606.20112","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.20112","created_at":"2026-06-19T16:13:03Z"},{"alias_kind":"arxiv_version","alias_value":"2606.20112v1","created_at":"2026-06-19T16:13:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.20112","created_at":"2026-06-19T16:13:03Z"},{"alias_kind":"pith_short_12","alias_value":"3DZCRDPNTHVO","created_at":"2026-06-19T16:13:03Z"},{"alias_kind":"pith_short_16","alias_value":"3DZCRDPNTHVOE6E4","created_at":"2026-06-19T16:13:03Z"},{"alias_kind":"pith_short_8","alias_value":"3DZCRDPN","created_at":"2026-06-19T16:13:03Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:3DZCRDPNTHVOE6E4D3TEEJPGHC","target":"record","payload":{"canonical_record":{"source":{"id":"2606.20112","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-18T11:35:11Z","cross_cats_sorted":["eess.IV"],"title_canon_sha256":"8d295a4794f860c1da03c12607eb090d0ad1ec82cf56fcb15e4dfc722ec866c8","abstract_canon_sha256":"ad8974b3e77316cd9b0a4d04bd18eedea69b3140417c9db26646d90e980701ff"},"schema_version":"1.0"},"canonical_sha256":"d8f2288ded99eae2789c1ee64225e638acfae50b571412e4bfe53f93063d43f2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-19T16:13:03.169935Z","signature_b64":"ItGaT3Vx1BL3dHocCEdxmnJtwaX3LCTDxD7aeIlXl8lxH5bWCObgFT6MQUyWRqTLO3OGd3oQ/hSsp+nsQtaEDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d8f2288ded99eae2789c1ee64225e638acfae50b571412e4bfe53f93063d43f2","last_reissued_at":"2026-06-19T16:13:03.169532Z","signature_status":"signed_v1","first_computed_at":"2026-06-19T16:13:03.169532Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.20112","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-06-19T16:13:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qV9lab0F4MQntbk1Ikb98SIq4CXsKJ9cFtvIflVuXZnbcpXP3+Tpv8/WC7pk+9rm/syzfQM1/y8WSt1XGmvUCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-28T00:43:46.164310Z"},"content_sha256":"2cfff63a24be560c005fee84a36fecdc4d0e54feea51e7e90d6a2710ebd3584f","schema_version":"1.0","event_id":"sha256:2cfff63a24be560c005fee84a36fecdc4d0e54feea51e7e90d6a2710ebd3584f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:3DZCRDPNTHVOE6E4D3TEEJPGHC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Pixel-Level Residual Diffusion Transformer: Scalable 3D CT Volume Generation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["eess.IV"],"primary_cat":"cs.CV","authors_text":"Krista A. Ehinger, Markus Hiller, Tom Drummond, Zhenkai Zhang","submitted_at":"2026-06-18T11:35:11Z","abstract_excerpt":"Generating high-resolution 3D CT volumes with fine details remains challenging due to substantial computational demands and optimization difficulties inherent to existing generative models. In this paper, we propose the Pixel-Level Residual Diffusion Transformer (PRDiT), a scalable generative framework that synthesizes high-quality 3D medical volumes directly at voxel-level. PRDiT introduces a two-stage training architecture comprising 1) a local denoiser in the form of an MLP-based blind estimator operating on overlapping 3D patches to separate low-frequency structures efficiently, and 2) a g"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.20112","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/2606.20112/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-06-19T16:13:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QKjWCC6BBpr+e1pahrDxeEbOz03ql8ZpO+FjsYSj91MBj3IXM4IhrHjWTgojYlVw7/FYFeN3ynI6Efc0N+0kCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-28T00:43:46.164697Z"},"content_sha256":"5a36c175bda46bc15ce4443139b91745f88e973237930ea49bdb75482a52c141","schema_version":"1.0","event_id":"sha256:5a36c175bda46bc15ce4443139b91745f88e973237930ea49bdb75482a52c141"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3DZCRDPNTHVOE6E4D3TEEJPGHC/bundle.json","state_url":"https://pith.science/pith/3DZCRDPNTHVOE6E4D3TEEJPGHC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3DZCRDPNTHVOE6E4D3TEEJPGHC/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-28T00:43:46Z","links":{"resolver":"https://pith.science/pith/3DZCRDPNTHVOE6E4D3TEEJPGHC","bundle":"https://pith.science/pith/3DZCRDPNTHVOE6E4D3TEEJPGHC/bundle.json","state":"https://pith.science/pith/3DZCRDPNTHVOE6E4D3TEEJPGHC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3DZCRDPNTHVOE6E4D3TEEJPGHC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:3DZCRDPNTHVOE6E4D3TEEJPGHC","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":"ad8974b3e77316cd9b0a4d04bd18eedea69b3140417c9db26646d90e980701ff","cross_cats_sorted":["eess.IV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-18T11:35:11Z","title_canon_sha256":"8d295a4794f860c1da03c12607eb090d0ad1ec82cf56fcb15e4dfc722ec866c8"},"schema_version":"1.0","source":{"id":"2606.20112","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.20112","created_at":"2026-06-19T16:13:03Z"},{"alias_kind":"arxiv_version","alias_value":"2606.20112v1","created_at":"2026-06-19T16:13:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.20112","created_at":"2026-06-19T16:13:03Z"},{"alias_kind":"pith_short_12","alias_value":"3DZCRDPNTHVO","created_at":"2026-06-19T16:13:03Z"},{"alias_kind":"pith_short_16","alias_value":"3DZCRDPNTHVOE6E4","created_at":"2026-06-19T16:13:03Z"},{"alias_kind":"pith_short_8","alias_value":"3DZCRDPN","created_at":"2026-06-19T16:13:03Z"}],"graph_snapshots":[{"event_id":"sha256:5a36c175bda46bc15ce4443139b91745f88e973237930ea49bdb75482a52c141","target":"graph","created_at":"2026-06-19T16:13:03Z","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/2606.20112/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Generating high-resolution 3D CT volumes with fine details remains challenging due to substantial computational demands and optimization difficulties inherent to existing generative models. In this paper, we propose the Pixel-Level Residual Diffusion Transformer (PRDiT), a scalable generative framework that synthesizes high-quality 3D medical volumes directly at voxel-level. PRDiT introduces a two-stage training architecture comprising 1) a local denoiser in the form of an MLP-based blind estimator operating on overlapping 3D patches to separate low-frequency structures efficiently, and 2) a g","authors_text":"Krista A. Ehinger, Markus Hiller, Tom Drummond, Zhenkai Zhang","cross_cats":["eess.IV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-18T11:35:11Z","title":"Pixel-Level Residual Diffusion Transformer: Scalable 3D CT Volume Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.20112","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":"sha256:2cfff63a24be560c005fee84a36fecdc4d0e54feea51e7e90d6a2710ebd3584f","target":"record","created_at":"2026-06-19T16:13:03Z","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":"ad8974b3e77316cd9b0a4d04bd18eedea69b3140417c9db26646d90e980701ff","cross_cats_sorted":["eess.IV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-18T11:35:11Z","title_canon_sha256":"8d295a4794f860c1da03c12607eb090d0ad1ec82cf56fcb15e4dfc722ec866c8"},"schema_version":"1.0","source":{"id":"2606.20112","kind":"arxiv","version":1}},"canonical_sha256":"d8f2288ded99eae2789c1ee64225e638acfae50b571412e4bfe53f93063d43f2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d8f2288ded99eae2789c1ee64225e638acfae50b571412e4bfe53f93063d43f2","first_computed_at":"2026-06-19T16:13:03.169532Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-19T16:13:03.169532Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ItGaT3Vx1BL3dHocCEdxmnJtwaX3LCTDxD7aeIlXl8lxH5bWCObgFT6MQUyWRqTLO3OGd3oQ/hSsp+nsQtaEDQ==","signature_status":"signed_v1","signed_at":"2026-06-19T16:13:03.169935Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.20112","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2cfff63a24be560c005fee84a36fecdc4d0e54feea51e7e90d6a2710ebd3584f","sha256:5a36c175bda46bc15ce4443139b91745f88e973237930ea49bdb75482a52c141"],"state_sha256":"5bc142df65230b6da2c4073000eac5eef6482100cbf3bb531d99a57e96a816ca"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JmdqE3ro5I78xmQzXkjh8vmcghjvfNDLu3LHN+H7ogMhEWklQiM+P83mEMIh6Bjo9nYK3CPjuZ/t0I53pbTBCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-28T00:43:46.166656Z","bundle_sha256":"4dcc9161bb83312e8f8b44028c3085e5068e7fc2151d1e494956ec3a93c001b1"}}