{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:BYD64EKPAKDALKGJU5HQWSGRK5","short_pith_number":"pith:BYD64EKP","canonical_record":{"source":{"id":"2310.03272","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-10-05T02:58:29Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"aa4a48227df9d5418184ef059d82fe73e06e7c972017510158242b75d3c3cc4d","abstract_canon_sha256":"7ff6a5a7b46bfdadcdc61f4d0bbfe006156a2ba0631de7ac9680a6799292c626"},"schema_version":"1.0"},"canonical_sha256":"0e07ee114f028605a8c9a74f0b48d1574fd21770a2b194492b5a96fb23e5df6a","source":{"kind":"arxiv","id":"2310.03272","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.03272","created_at":"2026-07-05T09:37:05Z"},{"alias_kind":"arxiv_version","alias_value":"2310.03272v4","created_at":"2026-07-05T09:37:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.03272","created_at":"2026-07-05T09:37:05Z"},{"alias_kind":"pith_short_12","alias_value":"BYD64EKPAKDA","created_at":"2026-07-05T09:37:05Z"},{"alias_kind":"pith_short_16","alias_value":"BYD64EKPAKDALKGJ","created_at":"2026-07-05T09:37:05Z"},{"alias_kind":"pith_short_8","alias_value":"BYD64EKP","created_at":"2026-07-05T09:37:05Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:BYD64EKPAKDALKGJU5HQWSGRK5","target":"record","payload":{"canonical_record":{"source":{"id":"2310.03272","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-10-05T02:58:29Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"aa4a48227df9d5418184ef059d82fe73e06e7c972017510158242b75d3c3cc4d","abstract_canon_sha256":"7ff6a5a7b46bfdadcdc61f4d0bbfe006156a2ba0631de7ac9680a6799292c626"},"schema_version":"1.0"},"canonical_sha256":"0e07ee114f028605a8c9a74f0b48d1574fd21770a2b194492b5a96fb23e5df6a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:37:05.281975Z","signature_b64":"S9j+je3JhpndicAA4rg+vxSa2Z9PMemcy5mcjjEcvunZrWvLOAeNG5FbPm0oeIj6P8qrREGqtZRakyGo5tswAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0e07ee114f028605a8c9a74f0b48d1574fd21770a2b194492b5a96fb23e5df6a","last_reissued_at":"2026-07-05T09:37:05.281489Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:37:05.281489Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2310.03272","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:37:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"u28Ipiy6qjtVICnMCcjFCE/u7x7tKepidd17nzROJzcoSE6l9Q9V3OziFTouII2oF574nVGMdeTNPp6BWtIkDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T13:13:10.128131Z"},"content_sha256":"f966d5a9a2aa518204f14595aad1d224b098df815c6f9c4ba46e54badd5a3104","schema_version":"1.0","event_id":"sha256:f966d5a9a2aa518204f14595aad1d224b098df815c6f9c4ba46e54badd5a3104"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:BYD64EKPAKDALKGJU5HQWSGRK5","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"T-GAE: Transferable Graph Autoencoder for Network Alignment","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Alejandro Ribeiro, Charilaos I. Kanatsoulis, Jiashu He","submitted_at":"2023-10-05T02:58:29Z","abstract_excerpt":"Network alignment is the task of establishing one-to-one correspondences between the nodes of different graphs. Although finding a plethora of applications in high-impact domains, this task is known to be NP-hard in its general form. Existing optimization algorithms do not scale up as the size of the graphs increases. While being able to reduce the matching complexity, current GNN approaches fit a deep neural network on each graph and requires re-train on unseen samples, which is time and memory inefficient. To tackle both challenges we propose T-GAE, a transferable graph autoencoder framework"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.03272","kind":"arxiv","version":4},"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/2310.03272/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":"2026-07-05T09:37:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EibjoVymu2iCQhB74aWLVfJq/WnGjfjR2qp6DOHC9UrGogozwxzAjSW6GASXl/R+SdblqwP3ACNT50yWFm4tAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T13:13:10.128640Z"},"content_sha256":"1e970ae31c72c7b8538a72ede9bb59874895180016aa105e988ceb8dd3e602a7","schema_version":"1.0","event_id":"sha256:1e970ae31c72c7b8538a72ede9bb59874895180016aa105e988ceb8dd3e602a7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BYD64EKPAKDALKGJU5HQWSGRK5/bundle.json","state_url":"https://pith.science/pith/BYD64EKPAKDALKGJU5HQWSGRK5/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BYD64EKPAKDALKGJU5HQWSGRK5/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":"2026-08-08T13:13:10Z","links":{"resolver":"https://pith.science/pith/BYD64EKPAKDALKGJU5HQWSGRK5","bundle":"https://pith.science/pith/BYD64EKPAKDALKGJU5HQWSGRK5/bundle.json","state":"https://pith.science/pith/BYD64EKPAKDALKGJU5HQWSGRK5/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BYD64EKPAKDALKGJU5HQWSGRK5/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:BYD64EKPAKDALKGJU5HQWSGRK5","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":"7ff6a5a7b46bfdadcdc61f4d0bbfe006156a2ba0631de7ac9680a6799292c626","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-10-05T02:58:29Z","title_canon_sha256":"aa4a48227df9d5418184ef059d82fe73e06e7c972017510158242b75d3c3cc4d"},"schema_version":"1.0","source":{"id":"2310.03272","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.03272","created_at":"2026-07-05T09:37:05Z"},{"alias_kind":"arxiv_version","alias_value":"2310.03272v4","created_at":"2026-07-05T09:37:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.03272","created_at":"2026-07-05T09:37:05Z"},{"alias_kind":"pith_short_12","alias_value":"BYD64EKPAKDA","created_at":"2026-07-05T09:37:05Z"},{"alias_kind":"pith_short_16","alias_value":"BYD64EKPAKDALKGJ","created_at":"2026-07-05T09:37:05Z"},{"alias_kind":"pith_short_8","alias_value":"BYD64EKP","created_at":"2026-07-05T09:37:05Z"}],"graph_snapshots":[{"event_id":"sha256:1e970ae31c72c7b8538a72ede9bb59874895180016aa105e988ceb8dd3e602a7","target":"graph","created_at":"2026-07-05T09:37:05Z","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/2310.03272/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Network alignment is the task of establishing one-to-one correspondences between the nodes of different graphs. Although finding a plethora of applications in high-impact domains, this task is known to be NP-hard in its general form. Existing optimization algorithms do not scale up as the size of the graphs increases. While being able to reduce the matching complexity, current GNN approaches fit a deep neural network on each graph and requires re-train on unseen samples, which is time and memory inefficient. To tackle both challenges we propose T-GAE, a transferable graph autoencoder framework","authors_text":"Alejandro Ribeiro, Charilaos I. Kanatsoulis, Jiashu He","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-10-05T02:58:29Z","title":"T-GAE: Transferable Graph Autoencoder for Network Alignment"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.03272","kind":"arxiv","version":4},"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:f966d5a9a2aa518204f14595aad1d224b098df815c6f9c4ba46e54badd5a3104","target":"record","created_at":"2026-07-05T09:37:05Z","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":"7ff6a5a7b46bfdadcdc61f4d0bbfe006156a2ba0631de7ac9680a6799292c626","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-10-05T02:58:29Z","title_canon_sha256":"aa4a48227df9d5418184ef059d82fe73e06e7c972017510158242b75d3c3cc4d"},"schema_version":"1.0","source":{"id":"2310.03272","kind":"arxiv","version":4}},"canonical_sha256":"0e07ee114f028605a8c9a74f0b48d1574fd21770a2b194492b5a96fb23e5df6a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0e07ee114f028605a8c9a74f0b48d1574fd21770a2b194492b5a96fb23e5df6a","first_computed_at":"2026-07-05T09:37:05.281489Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:37:05.281489Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"S9j+je3JhpndicAA4rg+vxSa2Z9PMemcy5mcjjEcvunZrWvLOAeNG5FbPm0oeIj6P8qrREGqtZRakyGo5tswAA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:37:05.281975Z","signed_message":"canonical_sha256_bytes"},"source_id":"2310.03272","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f966d5a9a2aa518204f14595aad1d224b098df815c6f9c4ba46e54badd5a3104","sha256:1e970ae31c72c7b8538a72ede9bb59874895180016aa105e988ceb8dd3e602a7"],"state_sha256":"c56e73971e8e59163b3bd8b841c8f4964695924bd6f7e0710bb67f85fc0f3dd5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"L0ZTKSu2WI9m25B1SFV7p5ohsCDN/zxLmBUxSuGdWnsZiozYwMTM2CeP6EykdmLS5GjfgRffN7r47pdby3GsAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T13:13:10.133210Z","bundle_sha256":"c5730b1f7b80405b3b4782bb7a6a4ac08584ae771a9cc246bf8bd6bd65c9a5fa"}}