{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:5CVX5VO7L7V2QLOR22H32V3LLD","short_pith_number":"pith:5CVX5VO7","canonical_record":{"source":{"id":"2308.13982","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-08-27T01:19:19Z","cross_cats_sorted":[],"title_canon_sha256":"4e75fcc53abd1a8f0697d0e920ccec35864baca475f23cadf9f7f87b758edb10","abstract_canon_sha256":"545fd48a068a992931e7eefbe3fa5689c7072d007d3d0919260507c82b2879d3"},"schema_version":"1.0"},"canonical_sha256":"e8ab7ed5df5feba82dd1d68fbd576b58d4ad7b00299670b96e77b23a1d1bd7f5","source":{"kind":"arxiv","id":"2308.13982","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2308.13982","created_at":"2026-07-05T06:45:07Z"},{"alias_kind":"arxiv_version","alias_value":"2308.13982v1","created_at":"2026-07-05T06:45:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.13982","created_at":"2026-07-05T06:45:07Z"},{"alias_kind":"pith_short_12","alias_value":"5CVX5VO7L7V2","created_at":"2026-07-05T06:45:07Z"},{"alias_kind":"pith_short_16","alias_value":"5CVX5VO7L7V2QLOR","created_at":"2026-07-05T06:45:07Z"},{"alias_kind":"pith_short_8","alias_value":"5CVX5VO7","created_at":"2026-07-05T06:45:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:5CVX5VO7L7V2QLOR22H32V3LLD","target":"record","payload":{"canonical_record":{"source":{"id":"2308.13982","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-08-27T01:19:19Z","cross_cats_sorted":[],"title_canon_sha256":"4e75fcc53abd1a8f0697d0e920ccec35864baca475f23cadf9f7f87b758edb10","abstract_canon_sha256":"545fd48a068a992931e7eefbe3fa5689c7072d007d3d0919260507c82b2879d3"},"schema_version":"1.0"},"canonical_sha256":"e8ab7ed5df5feba82dd1d68fbd576b58d4ad7b00299670b96e77b23a1d1bd7f5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:45:07.899952Z","signature_b64":"LIEQpYOsrn1LhW0K4y3nMZ8rPed7Ztu+N/t5vZlai8dqcMzmXtBLD2X0OKdqZi7EprOLO93KUS1oeguXvie4DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e8ab7ed5df5feba82dd1d68fbd576b58d4ad7b00299670b96e77b23a1d1bd7f5","last_reissued_at":"2026-07-05T06:45:07.899424Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:45:07.899424Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2308.13982","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":"2026-07-05T06:45:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MPatLTGi6LwrqKy60kUF5iSqVRSf7yqCVM5iGBa9w9IaYynkAi/qZKwkSu9nI2WsmCQNT3BcKzYocAAxob7RCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T16:26:42.238846Z"},"content_sha256":"2364ac87889df12dc1e208e2f8f970f5126c1d6f49a0721a72ba4e04c814da1a","schema_version":"1.0","event_id":"sha256:2364ac87889df12dc1e208e2f8f970f5126c1d6f49a0721a72ba4e04c814da1a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:5CVX5VO7L7V2QLOR22H32V3LLD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Universal Graph Continual Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Bao-Sinh Nguyen, Do Viet Tung, Duy-Hung Nguyen, Hung Le, Huy Hoang Nguyen, Thanh Duc Hoang","submitted_at":"2023-08-27T01:19:19Z","abstract_excerpt":"We address catastrophic forgetting issues in graph learning as incoming data transits from one to another graph distribution. Whereas prior studies primarily tackle one setting of graph continual learning such as incremental node classification, we focus on a universal approach wherein each data point in a task can be a node or a graph, and the task varies from node to graph classification. We propose a novel method that enables graph neural networks to excel in this universal setting. Our approach perseveres knowledge about past tasks through a rehearsal mechanism that maintains local and glo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.13982","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/2308.13982/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":"2026-07-05T06:45:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sCMH3sCRehdoVQPei+8pWBOc/gEc1gTy9UbAaOtkeUIBGGctqwQ99UAg+vbeMwwJSEds9pqWWH/53R8oumRLCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T16:26:42.239464Z"},"content_sha256":"11121c6fea137b359aded947dc9189787721d26027a785c4d524cd0edf7396c3","schema_version":"1.0","event_id":"sha256:11121c6fea137b359aded947dc9189787721d26027a785c4d524cd0edf7396c3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5CVX5VO7L7V2QLOR22H32V3LLD/bundle.json","state_url":"https://pith.science/pith/5CVX5VO7L7V2QLOR22H32V3LLD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5CVX5VO7L7V2QLOR22H32V3LLD/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":"2026-08-07T16:26:42Z","links":{"resolver":"https://pith.science/pith/5CVX5VO7L7V2QLOR22H32V3LLD","bundle":"https://pith.science/pith/5CVX5VO7L7V2QLOR22H32V3LLD/bundle.json","state":"https://pith.science/pith/5CVX5VO7L7V2QLOR22H32V3LLD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5CVX5VO7L7V2QLOR22H32V3LLD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:5CVX5VO7L7V2QLOR22H32V3LLD","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":"545fd48a068a992931e7eefbe3fa5689c7072d007d3d0919260507c82b2879d3","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-08-27T01:19:19Z","title_canon_sha256":"4e75fcc53abd1a8f0697d0e920ccec35864baca475f23cadf9f7f87b758edb10"},"schema_version":"1.0","source":{"id":"2308.13982","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2308.13982","created_at":"2026-07-05T06:45:07Z"},{"alias_kind":"arxiv_version","alias_value":"2308.13982v1","created_at":"2026-07-05T06:45:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.13982","created_at":"2026-07-05T06:45:07Z"},{"alias_kind":"pith_short_12","alias_value":"5CVX5VO7L7V2","created_at":"2026-07-05T06:45:07Z"},{"alias_kind":"pith_short_16","alias_value":"5CVX5VO7L7V2QLOR","created_at":"2026-07-05T06:45:07Z"},{"alias_kind":"pith_short_8","alias_value":"5CVX5VO7","created_at":"2026-07-05T06:45:07Z"}],"graph_snapshots":[{"event_id":"sha256:11121c6fea137b359aded947dc9189787721d26027a785c4d524cd0edf7396c3","target":"graph","created_at":"2026-07-05T06:45:07Z","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/2308.13982/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We address catastrophic forgetting issues in graph learning as incoming data transits from one to another graph distribution. Whereas prior studies primarily tackle one setting of graph continual learning such as incremental node classification, we focus on a universal approach wherein each data point in a task can be a node or a graph, and the task varies from node to graph classification. We propose a novel method that enables graph neural networks to excel in this universal setting. Our approach perseveres knowledge about past tasks through a rehearsal mechanism that maintains local and glo","authors_text":"Bao-Sinh Nguyen, Do Viet Tung, Duy-Hung Nguyen, Hung Le, Huy Hoang Nguyen, Thanh Duc Hoang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-08-27T01:19:19Z","title":"Universal Graph Continual Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.13982","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":"sha256:2364ac87889df12dc1e208e2f8f970f5126c1d6f49a0721a72ba4e04c814da1a","target":"record","created_at":"2026-07-05T06:45:07Z","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":"545fd48a068a992931e7eefbe3fa5689c7072d007d3d0919260507c82b2879d3","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-08-27T01:19:19Z","title_canon_sha256":"4e75fcc53abd1a8f0697d0e920ccec35864baca475f23cadf9f7f87b758edb10"},"schema_version":"1.0","source":{"id":"2308.13982","kind":"arxiv","version":1}},"canonical_sha256":"e8ab7ed5df5feba82dd1d68fbd576b58d4ad7b00299670b96e77b23a1d1bd7f5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e8ab7ed5df5feba82dd1d68fbd576b58d4ad7b00299670b96e77b23a1d1bd7f5","first_computed_at":"2026-07-05T06:45:07.899424Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:45:07.899424Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"LIEQpYOsrn1LhW0K4y3nMZ8rPed7Ztu+N/t5vZlai8dqcMzmXtBLD2X0OKdqZi7EprOLO93KUS1oeguXvie4DA==","signature_status":"signed_v1","signed_at":"2026-07-05T06:45:07.899952Z","signed_message":"canonical_sha256_bytes"},"source_id":"2308.13982","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2364ac87889df12dc1e208e2f8f970f5126c1d6f49a0721a72ba4e04c814da1a","sha256:11121c6fea137b359aded947dc9189787721d26027a785c4d524cd0edf7396c3"],"state_sha256":"e38791a2189f4e9ef8982def5cf79e44395b0f14d9e777c72537712a7711a614"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jSaQkw/sIW4qURw/c9d1ylYkbcEc0wz8zaPQj3ocuboG1A7Blc33fic6fS2o4HbxRxBsrxzA3Ns9Isxg43fFDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T16:26:42.244519Z","bundle_sha256":"313a52c91f508ba1bbabc54890e4deab3f84ca70bbb42d99ecb22edbaa589ad3"}}