{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:YLNLMVJWDUA2DGH3LH66MS5NKR","short_pith_number":"pith:YLNLMVJW","canonical_record":{"source":{"id":"2607.11533","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-13T13:18:21Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"aac306ef77c339230ee0d2d3ba5ddb4200aadc486222c048061e2b04ddbf5c5a","abstract_canon_sha256":"228d7ede6cdddc4ece08ec7a4c876529f5b8e699f263b397dfca76df0ecca5ae"},"schema_version":"1.0"},"canonical_sha256":"c2dab655361d01a198fb59fde64bad5446507915518e8935df89143f9ad5221f","source":{"kind":"arxiv","id":"2607.11533","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.11533","created_at":"2026-07-14T02:22:09Z"},{"alias_kind":"arxiv_version","alias_value":"2607.11533v1","created_at":"2026-07-14T02:22:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.11533","created_at":"2026-07-14T02:22:09Z"},{"alias_kind":"pith_short_12","alias_value":"YLNLMVJWDUA2","created_at":"2026-07-14T02:22:09Z"},{"alias_kind":"pith_short_16","alias_value":"YLNLMVJWDUA2DGH3","created_at":"2026-07-14T02:22:09Z"},{"alias_kind":"pith_short_8","alias_value":"YLNLMVJW","created_at":"2026-07-14T02:22:09Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:YLNLMVJWDUA2DGH3LH66MS5NKR","target":"record","payload":{"canonical_record":{"source":{"id":"2607.11533","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-13T13:18:21Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"aac306ef77c339230ee0d2d3ba5ddb4200aadc486222c048061e2b04ddbf5c5a","abstract_canon_sha256":"228d7ede6cdddc4ece08ec7a4c876529f5b8e699f263b397dfca76df0ecca5ae"},"schema_version":"1.0"},"canonical_sha256":"c2dab655361d01a198fb59fde64bad5446507915518e8935df89143f9ad5221f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-14T02:22:09.529873Z","signature_b64":"XvBtTcoHVXI6Z6odSTRF8zi6ivSUwdU/TkrOFGSh8wXUiwleKJtNfGO2W2PaPzzSLgLtrorcm79HmYEEK4k+Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c2dab655361d01a198fb59fde64bad5446507915518e8935df89143f9ad5221f","last_reissued_at":"2026-07-14T02:22:09.528985Z","signature_status":"signed_v1","first_computed_at":"2026-07-14T02:22:09.528985Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2607.11533","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":"2026-07-14T02:22:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SpI2Y472ecMQwisjDKUcYdGYl7eTqbCT4PIxEirRaX/md8nFhxIiTmoVFtGBFQjruQ34q/f4qsJh2W5tvPetBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T20:01:54.434788Z"},"content_sha256":"e9d4219b83a825036dea8c59a6de32c88fb4b49c568a3bdba5a0ce74e1c620b4","schema_version":"1.0","event_id":"sha256:e9d4219b83a825036dea8c59a6de32c88fb4b49c568a3bdba5a0ce74e1c620b4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:YLNLMVJWDUA2DGH3LH66MS5NKR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Adaptive Routing for Efficient Diffusion Transformer-Based PNI Prediction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Anna Jung, Dohyun Kweon, Hyuk-jae Lee, Hyunsu Go, Induk Um, Jina Jeong, Jinyong Jun, Junga Kim, Ken Ying-Kai Liao, Kyeonghun Kim, Nam-Joon Kim, Pa Hong, Suah Park, Sungha Park, Won Jae Lee, Woo Kyoung Jeong, Youngung Han, Yului Jeong","submitted_at":"2026-07-13T13:18:21Z","abstract_excerpt":"Perineural invasion (PNI) is a critical prognostic factor in cholangiocarcinoma. However, its preoperative prediction from magnetic resonance imaging (MRI) remains challenging due to subtle imaging features that extend beyond tumor boundaries into surrounding regions. Conventional convolutional neural networks are limited in capturing long-range spatial dependencies. Transformer-based architectures improve global modeling of volumetric MRI by aggregating spatially distributed contextual cues, yet capturing subtle and noise-sensitive patterns in peritumoral regions remains challenging. Diffusio"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.11533","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/2607.11533/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":"2026-07-14T02:22:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GYO44fxyoZqlYw3M2Z7KYZqflWczdpk/+LMOdXGqQ4+vfIL810AeJTM+TlQrLVIJfleq2bQkFYdX0hdhnGJ8Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T20:01:54.435172Z"},"content_sha256":"e47cbc721efce7917c09939815cd8a47a06e718c1244502f43eca76bcc6d2c2f","schema_version":"1.0","event_id":"sha256:e47cbc721efce7917c09939815cd8a47a06e718c1244502f43eca76bcc6d2c2f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YLNLMVJWDUA2DGH3LH66MS5NKR/bundle.json","state_url":"https://pith.science/pith/YLNLMVJWDUA2DGH3LH66MS5NKR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YLNLMVJWDUA2DGH3LH66MS5NKR/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":"2026-08-04T20:01:54Z","links":{"resolver":"https://pith.science/pith/YLNLMVJWDUA2DGH3LH66MS5NKR","bundle":"https://pith.science/pith/YLNLMVJWDUA2DGH3LH66MS5NKR/bundle.json","state":"https://pith.science/pith/YLNLMVJWDUA2DGH3LH66MS5NKR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YLNLMVJWDUA2DGH3LH66MS5NKR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:YLNLMVJWDUA2DGH3LH66MS5NKR","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":"228d7ede6cdddc4ece08ec7a4c876529f5b8e699f263b397dfca76df0ecca5ae","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-13T13:18:21Z","title_canon_sha256":"aac306ef77c339230ee0d2d3ba5ddb4200aadc486222c048061e2b04ddbf5c5a"},"schema_version":"1.0","source":{"id":"2607.11533","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.11533","created_at":"2026-07-14T02:22:09Z"},{"alias_kind":"arxiv_version","alias_value":"2607.11533v1","created_at":"2026-07-14T02:22:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.11533","created_at":"2026-07-14T02:22:09Z"},{"alias_kind":"pith_short_12","alias_value":"YLNLMVJWDUA2","created_at":"2026-07-14T02:22:09Z"},{"alias_kind":"pith_short_16","alias_value":"YLNLMVJWDUA2DGH3","created_at":"2026-07-14T02:22:09Z"},{"alias_kind":"pith_short_8","alias_value":"YLNLMVJW","created_at":"2026-07-14T02:22:09Z"}],"graph_snapshots":[{"event_id":"sha256:e47cbc721efce7917c09939815cd8a47a06e718c1244502f43eca76bcc6d2c2f","target":"graph","created_at":"2026-07-14T02:22:09Z","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/2607.11533/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Perineural invasion (PNI) is a critical prognostic factor in cholangiocarcinoma. However, its preoperative prediction from magnetic resonance imaging (MRI) remains challenging due to subtle imaging features that extend beyond tumor boundaries into surrounding regions. Conventional convolutional neural networks are limited in capturing long-range spatial dependencies. Transformer-based architectures improve global modeling of volumetric MRI by aggregating spatially distributed contextual cues, yet capturing subtle and noise-sensitive patterns in peritumoral regions remains challenging. Diffusio","authors_text":"Anna Jung, Dohyun Kweon, Hyuk-jae Lee, Hyunsu Go, Induk Um, Jina Jeong, Jinyong Jun, Junga Kim, Ken Ying-Kai Liao, Kyeonghun Kim, Nam-Joon Kim, Pa Hong, Suah Park, Sungha Park, Won Jae Lee, Woo Kyoung Jeong, Youngung Han, Yului Jeong","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-13T13:18:21Z","title":"Adaptive Routing for Efficient Diffusion Transformer-Based PNI Prediction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.11533","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:e9d4219b83a825036dea8c59a6de32c88fb4b49c568a3bdba5a0ce74e1c620b4","target":"record","created_at":"2026-07-14T02:22:09Z","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":"228d7ede6cdddc4ece08ec7a4c876529f5b8e699f263b397dfca76df0ecca5ae","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-13T13:18:21Z","title_canon_sha256":"aac306ef77c339230ee0d2d3ba5ddb4200aadc486222c048061e2b04ddbf5c5a"},"schema_version":"1.0","source":{"id":"2607.11533","kind":"arxiv","version":1}},"canonical_sha256":"c2dab655361d01a198fb59fde64bad5446507915518e8935df89143f9ad5221f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c2dab655361d01a198fb59fde64bad5446507915518e8935df89143f9ad5221f","first_computed_at":"2026-07-14T02:22:09.528985Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-14T02:22:09.528985Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"XvBtTcoHVXI6Z6odSTRF8zi6ivSUwdU/TkrOFGSh8wXUiwleKJtNfGO2W2PaPzzSLgLtrorcm79HmYEEK4k+Bg==","signature_status":"signed_v1","signed_at":"2026-07-14T02:22:09.529873Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.11533","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e9d4219b83a825036dea8c59a6de32c88fb4b49c568a3bdba5a0ce74e1c620b4","sha256:e47cbc721efce7917c09939815cd8a47a06e718c1244502f43eca76bcc6d2c2f"],"state_sha256":"a80b2e1e5904a491be84c2b8a8338df9edb77992546b342d52d37099ece61152"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3seobm87CcEWxhCo/Sw/wArtf5irmBdIN9pI/bD4nPZoJVeMHoU2U6FGlQSMeZoy8YaWYzeAnEk53TpXwF2qBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T20:01:54.437555Z","bundle_sha256":"ca3d484b03467a5a7286f50dc1fe316e0a6fc2804131da9b268686f27250d009"}}