{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:P6PFSGSQ7WYYITWKLQUOGPS46J","short_pith_number":"pith:P6PFSGSQ","canonical_record":{"source":{"id":"2203.01932","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2022-03-02T21:10:24Z","cross_cats_sorted":["cs.CV","cs.LG"],"title_canon_sha256":"d070183fd591d747076762aa64a8ce628f6a991b44155758ff5dc90ae70022e9","abstract_canon_sha256":"5ba06bedeaea220e0dc14547783681946b9c36af841bae61101eb7dfbc907647"},"schema_version":"1.0"},"canonical_sha256":"7f9e591a50fdb1844eca5c28e33e5cf25c4a1e40b2bd73e115caeab43ab92783","source":{"kind":"arxiv","id":"2203.01932","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.01932","created_at":"2026-07-05T04:10:25Z"},{"alias_kind":"arxiv_version","alias_value":"2203.01932v2","created_at":"2026-07-05T04:10:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.01932","created_at":"2026-07-05T04:10:25Z"},{"alias_kind":"pith_short_12","alias_value":"P6PFSGSQ7WYY","created_at":"2026-07-05T04:10:25Z"},{"alias_kind":"pith_short_16","alias_value":"P6PFSGSQ7WYYITWK","created_at":"2026-07-05T04:10:25Z"},{"alias_kind":"pith_short_8","alias_value":"P6PFSGSQ","created_at":"2026-07-05T04:10:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:P6PFSGSQ7WYYITWKLQUOGPS46J","target":"record","payload":{"canonical_record":{"source":{"id":"2203.01932","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2022-03-02T21:10:24Z","cross_cats_sorted":["cs.CV","cs.LG"],"title_canon_sha256":"d070183fd591d747076762aa64a8ce628f6a991b44155758ff5dc90ae70022e9","abstract_canon_sha256":"5ba06bedeaea220e0dc14547783681946b9c36af841bae61101eb7dfbc907647"},"schema_version":"1.0"},"canonical_sha256":"7f9e591a50fdb1844eca5c28e33e5cf25c4a1e40b2bd73e115caeab43ab92783","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:10:25.974176Z","signature_b64":"Gw1u3y7SdtAc9tFsCDRj3X17yGPJUh2HjcAN76fnW74r54oH2sOK0FslNSDJF4IGOcYm90YNqxdP+AEwMz0WBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7f9e591a50fdb1844eca5c28e33e5cf25c4a1e40b2bd73e115caeab43ab92783","last_reissued_at":"2026-07-05T04:10:25.973718Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:10:25.973718Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2203.01932","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:10:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JJtraDleVAERXS/vuHRt0hSKTgVBEGQpctTYcEeTLPriubjqcp3k0e04PwOUy1nWql6zaeTWsUxmXwzovL31AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T21:50:06.759286Z"},"content_sha256":"a16927591a12b996eabdfd56df916370bf1f90b75213c96d2cc9d61d3237265a","schema_version":"1.0","event_id":"sha256:a16927591a12b996eabdfd56df916370bf1f90b75213c96d2cc9d61d3237265a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:P6PFSGSQ7WYYITWKLQUOGPS46J","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Contextual Attention Network: Transformer Meets U-Net","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV","cs.LG"],"primary_cat":"eess.IV","authors_text":"Dorit Merhof, Moein Heidari, Reza Azad, Yuli Wu","submitted_at":"2022-03-02T21:10:24Z","abstract_excerpt":"Currently, convolutional neural networks (CNN) (e.g., U-Net) have become the de facto standard and attained immense success in medical image segmentation. However, as a downside, CNN based methods are a double-edged sword as they fail to build long-range dependencies and global context connections due to the limited receptive field that stems from the intrinsic characteristics of the convolution operation. Hence, recent articles have exploited Transformer variants for medical image segmentation tasks which open up great opportunities due to their innate capability of capturing long-range corre"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.01932","kind":"arxiv","version":2},"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/2203.01932/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":"2026-07-05T04:10:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WPeCYOHLVAkJV3eumAd2aN1dAX8jp0qAYww1AtwvYsP7bpwVv8gs3n/D5fv9lOwqxWlACmrIav4XvZruhYejCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T21:50:06.759792Z"},"content_sha256":"c05aceb3c2320b206d0dea59cf0ab5343c55f0472eaa8b78dd676a45621df4c1","schema_version":"1.0","event_id":"sha256:c05aceb3c2320b206d0dea59cf0ab5343c55f0472eaa8b78dd676a45621df4c1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/P6PFSGSQ7WYYITWKLQUOGPS46J/bundle.json","state_url":"https://pith.science/pith/P6PFSGSQ7WYYITWKLQUOGPS46J/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/P6PFSGSQ7WYYITWKLQUOGPS46J/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":"2026-08-07T21:50:06Z","links":{"resolver":"https://pith.science/pith/P6PFSGSQ7WYYITWKLQUOGPS46J","bundle":"https://pith.science/pith/P6PFSGSQ7WYYITWKLQUOGPS46J/bundle.json","state":"https://pith.science/pith/P6PFSGSQ7WYYITWKLQUOGPS46J/state.json","well_known_bundle":"https://pith.science/.well-known/pith/P6PFSGSQ7WYYITWKLQUOGPS46J/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:P6PFSGSQ7WYYITWKLQUOGPS46J","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":"5ba06bedeaea220e0dc14547783681946b9c36af841bae61101eb7dfbc907647","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2022-03-02T21:10:24Z","title_canon_sha256":"d070183fd591d747076762aa64a8ce628f6a991b44155758ff5dc90ae70022e9"},"schema_version":"1.0","source":{"id":"2203.01932","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.01932","created_at":"2026-07-05T04:10:25Z"},{"alias_kind":"arxiv_version","alias_value":"2203.01932v2","created_at":"2026-07-05T04:10:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.01932","created_at":"2026-07-05T04:10:25Z"},{"alias_kind":"pith_short_12","alias_value":"P6PFSGSQ7WYY","created_at":"2026-07-05T04:10:25Z"},{"alias_kind":"pith_short_16","alias_value":"P6PFSGSQ7WYYITWK","created_at":"2026-07-05T04:10:25Z"},{"alias_kind":"pith_short_8","alias_value":"P6PFSGSQ","created_at":"2026-07-05T04:10:25Z"}],"graph_snapshots":[{"event_id":"sha256:c05aceb3c2320b206d0dea59cf0ab5343c55f0472eaa8b78dd676a45621df4c1","target":"graph","created_at":"2026-07-05T04:10:25Z","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/2203.01932/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Currently, convolutional neural networks (CNN) (e.g., U-Net) have become the de facto standard and attained immense success in medical image segmentation. However, as a downside, CNN based methods are a double-edged sword as they fail to build long-range dependencies and global context connections due to the limited receptive field that stems from the intrinsic characteristics of the convolution operation. Hence, recent articles have exploited Transformer variants for medical image segmentation tasks which open up great opportunities due to their innate capability of capturing long-range corre","authors_text":"Dorit Merhof, Moein Heidari, Reza Azad, Yuli Wu","cross_cats":["cs.CV","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2022-03-02T21:10:24Z","title":"Contextual Attention Network: Transformer Meets U-Net"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.01932","kind":"arxiv","version":2},"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:a16927591a12b996eabdfd56df916370bf1f90b75213c96d2cc9d61d3237265a","target":"record","created_at":"2026-07-05T04:10:25Z","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":"5ba06bedeaea220e0dc14547783681946b9c36af841bae61101eb7dfbc907647","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2022-03-02T21:10:24Z","title_canon_sha256":"d070183fd591d747076762aa64a8ce628f6a991b44155758ff5dc90ae70022e9"},"schema_version":"1.0","source":{"id":"2203.01932","kind":"arxiv","version":2}},"canonical_sha256":"7f9e591a50fdb1844eca5c28e33e5cf25c4a1e40b2bd73e115caeab43ab92783","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7f9e591a50fdb1844eca5c28e33e5cf25c4a1e40b2bd73e115caeab43ab92783","first_computed_at":"2026-07-05T04:10:25.973718Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:10:25.973718Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Gw1u3y7SdtAc9tFsCDRj3X17yGPJUh2HjcAN76fnW74r54oH2sOK0FslNSDJF4IGOcYm90YNqxdP+AEwMz0WBA==","signature_status":"signed_v1","signed_at":"2026-07-05T04:10:25.974176Z","signed_message":"canonical_sha256_bytes"},"source_id":"2203.01932","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a16927591a12b996eabdfd56df916370bf1f90b75213c96d2cc9d61d3237265a","sha256:c05aceb3c2320b206d0dea59cf0ab5343c55f0472eaa8b78dd676a45621df4c1"],"state_sha256":"062ac4c9bef2df1af7d2dc63d0728a76781f57d6d5b9d8e1df3eddc213049c7f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UdKBAiy2GhmwOBX+5pRmKRSZd8h7/yc6h1NdiIo0agqLX+gOBeqmA2i/oPYdCKjiJbxp1xgGfb9UwiZVrUrLDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T21:50:06.763815Z","bundle_sha256":"0f677642297a85f9f2ca854576e5710ad7cd9ed94fb7f640045da02e012a8096"}}