{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:AAXVJXPRY6NKYCTBFEATJGVG7G","short_pith_number":"pith:AAXVJXPR","canonical_record":{"source":{"id":"2412.11458","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-16T05:32:28Z","cross_cats_sorted":[],"title_canon_sha256":"0438148ae6a953fe8cac50046cd62a036c99b1ea6a46d44e1d1108f0d2fda49d","abstract_canon_sha256":"fa2b033b74ebc2185e3537ce0c03a835a6045bed63ebc81626a39167b936e499"},"schema_version":"1.0"},"canonical_sha256":"002f54ddf1c79aac0a612901349aa6f9a149b08e13df1eee9b9b577b4a2630f8","source":{"kind":"arxiv","id":"2412.11458","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.11458","created_at":"2026-07-05T09:49:33Z"},{"alias_kind":"arxiv_version","alias_value":"2412.11458v1","created_at":"2026-07-05T09:49:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.11458","created_at":"2026-07-05T09:49:33Z"},{"alias_kind":"pith_short_12","alias_value":"AAXVJXPRY6NK","created_at":"2026-07-05T09:49:33Z"},{"alias_kind":"pith_short_16","alias_value":"AAXVJXPRY6NKYCTB","created_at":"2026-07-05T09:49:33Z"},{"alias_kind":"pith_short_8","alias_value":"AAXVJXPR","created_at":"2026-07-05T09:49:33Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:AAXVJXPRY6NKYCTBFEATJGVG7G","target":"record","payload":{"canonical_record":{"source":{"id":"2412.11458","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-16T05:32:28Z","cross_cats_sorted":[],"title_canon_sha256":"0438148ae6a953fe8cac50046cd62a036c99b1ea6a46d44e1d1108f0d2fda49d","abstract_canon_sha256":"fa2b033b74ebc2185e3537ce0c03a835a6045bed63ebc81626a39167b936e499"},"schema_version":"1.0"},"canonical_sha256":"002f54ddf1c79aac0a612901349aa6f9a149b08e13df1eee9b9b577b4a2630f8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:49:33.359242Z","signature_b64":"Nmh4u5hn0LELa/JhJt1WOEcZE+kPsjc25Rz5TdJjvLlny63T+5Aj0i0dqIxFHV5LUtPprdgOy1JIP6vciUyzCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"002f54ddf1c79aac0a612901349aa6f9a149b08e13df1eee9b9b577b4a2630f8","last_reissued_at":"2026-07-05T09:49:33.358858Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:49:33.358858Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.11458","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":"2026-07-05T09:49:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oOzDs8zH2tw8NAccmv5qtmS3xFPUh7ZCYBqlvZNAHPCbL3/B7g32vBU8ae0RNLZB4wgRLCqzcvcKQTTWV8r6Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T19:10:21.183358Z"},"content_sha256":"892d112e41599ee5da9299d99a3e5877c4718aad62422300fa49a9222feb6664","schema_version":"1.0","event_id":"sha256:892d112e41599ee5da9299d99a3e5877c4718aad62422300fa49a9222feb6664"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:AAXVJXPRY6NKYCTBFEATJGVG7G","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"HResFormer: Hybrid Residual Transformer for Volumetric Medical Image Segmentation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Sucheng Ren, Xiaomeng Li","submitted_at":"2024-12-16T05:32:28Z","abstract_excerpt":"Vision Transformer shows great superiority in medical image segmentation due to the ability in learning long-range dependency. For medical image segmentation from 3D data, such as computed tomography (CT), existing methods can be broadly classified into 2D-based and 3D-based methods. One key limitation in 2D-based methods is that the intra-slice information is ignored, while the limitation in 3D-based methods is the high computation cost and memory consumption, resulting in a limited feature representation for inner-slice information. During the clinical examination, radiologists primarily use"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.11458","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/2412.11458/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":"2026-07-05T09:49:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zXdqAS4toAJeVviAjqLteBrDLzb8HwQ8QBkxg4Tf2DygpSwnPhsZLMY92bocz1GyIY5177Ch+AjRWuBjDV9RAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T19:10:21.183955Z"},"content_sha256":"fc836b7bc340c2b215057c15b4f92bfa60ab4121ce9e98525f9cfb30589319d9","schema_version":"1.0","event_id":"sha256:fc836b7bc340c2b215057c15b4f92bfa60ab4121ce9e98525f9cfb30589319d9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AAXVJXPRY6NKYCTBFEATJGVG7G/bundle.json","state_url":"https://pith.science/pith/AAXVJXPRY6NKYCTBFEATJGVG7G/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AAXVJXPRY6NKYCTBFEATJGVG7G/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":"2026-08-17T19:10:21Z","links":{"resolver":"https://pith.science/pith/AAXVJXPRY6NKYCTBFEATJGVG7G","bundle":"https://pith.science/pith/AAXVJXPRY6NKYCTBFEATJGVG7G/bundle.json","state":"https://pith.science/pith/AAXVJXPRY6NKYCTBFEATJGVG7G/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AAXVJXPRY6NKYCTBFEATJGVG7G/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:AAXVJXPRY6NKYCTBFEATJGVG7G","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":"fa2b033b74ebc2185e3537ce0c03a835a6045bed63ebc81626a39167b936e499","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-16T05:32:28Z","title_canon_sha256":"0438148ae6a953fe8cac50046cd62a036c99b1ea6a46d44e1d1108f0d2fda49d"},"schema_version":"1.0","source":{"id":"2412.11458","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.11458","created_at":"2026-07-05T09:49:33Z"},{"alias_kind":"arxiv_version","alias_value":"2412.11458v1","created_at":"2026-07-05T09:49:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.11458","created_at":"2026-07-05T09:49:33Z"},{"alias_kind":"pith_short_12","alias_value":"AAXVJXPRY6NK","created_at":"2026-07-05T09:49:33Z"},{"alias_kind":"pith_short_16","alias_value":"AAXVJXPRY6NKYCTB","created_at":"2026-07-05T09:49:33Z"},{"alias_kind":"pith_short_8","alias_value":"AAXVJXPR","created_at":"2026-07-05T09:49:33Z"}],"graph_snapshots":[{"event_id":"sha256:fc836b7bc340c2b215057c15b4f92bfa60ab4121ce9e98525f9cfb30589319d9","target":"graph","created_at":"2026-07-05T09:49:33Z","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/2412.11458/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Vision Transformer shows great superiority in medical image segmentation due to the ability in learning long-range dependency. For medical image segmentation from 3D data, such as computed tomography (CT), existing methods can be broadly classified into 2D-based and 3D-based methods. One key limitation in 2D-based methods is that the intra-slice information is ignored, while the limitation in 3D-based methods is the high computation cost and memory consumption, resulting in a limited feature representation for inner-slice information. During the clinical examination, radiologists primarily use","authors_text":"Sucheng Ren, Xiaomeng Li","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-16T05:32:28Z","title":"HResFormer: Hybrid Residual Transformer for Volumetric Medical Image Segmentation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.11458","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":"sha256:892d112e41599ee5da9299d99a3e5877c4718aad62422300fa49a9222feb6664","target":"record","created_at":"2026-07-05T09:49:33Z","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":"fa2b033b74ebc2185e3537ce0c03a835a6045bed63ebc81626a39167b936e499","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-16T05:32:28Z","title_canon_sha256":"0438148ae6a953fe8cac50046cd62a036c99b1ea6a46d44e1d1108f0d2fda49d"},"schema_version":"1.0","source":{"id":"2412.11458","kind":"arxiv","version":1}},"canonical_sha256":"002f54ddf1c79aac0a612901349aa6f9a149b08e13df1eee9b9b577b4a2630f8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"002f54ddf1c79aac0a612901349aa6f9a149b08e13df1eee9b9b577b4a2630f8","first_computed_at":"2026-07-05T09:49:33.358858Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:49:33.358858Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Nmh4u5hn0LELa/JhJt1WOEcZE+kPsjc25Rz5TdJjvLlny63T+5Aj0i0dqIxFHV5LUtPprdgOy1JIP6vciUyzCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:49:33.359242Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.11458","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:892d112e41599ee5da9299d99a3e5877c4718aad62422300fa49a9222feb6664","sha256:fc836b7bc340c2b215057c15b4f92bfa60ab4121ce9e98525f9cfb30589319d9"],"state_sha256":"9a90715fa97970abea00a506d5cabaae123f1a1047369527a2b42f2b45e08e10"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/+mT7HaVfC2sOlbk0u4GukCWAKSPJfM7sqaHdnLHgAhJc6BK5oFfGmZQKNbMAjcSEKU8xkhco8lNb+qF98QeDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-17T19:10:21.188938Z","bundle_sha256":"244ae828791963172aedfb3a4c0fff777f67b761e340cde44e54b7e0ea053442"}}