{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:FDXJ5VJ4CTO4GSOHD7I6ULXFUE","short_pith_number":"pith:FDXJ5VJ4","canonical_record":{"source":{"id":"2401.16386","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-01-29T18:27:52Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"900d146919bf3b665f55cc988947032a2e0b9e19696c8b8e38e5cc0eccb6b282","abstract_canon_sha256":"829bb629172c729bd04077952c2f142261054ee6ac613d6dc9442ad2bfa2829b"},"schema_version":"1.0"},"canonical_sha256":"28ee9ed53c14ddc349c71fd1ea2ee5a13a11b4c1db017e888eced9d590d6f9e8","source":{"kind":"arxiv","id":"2401.16386","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2401.16386","created_at":"2026-07-05T08:11:00Z"},{"alias_kind":"arxiv_version","alias_value":"2401.16386v2","created_at":"2026-07-05T08:11:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.16386","created_at":"2026-07-05T08:11:00Z"},{"alias_kind":"pith_short_12","alias_value":"FDXJ5VJ4CTO4","created_at":"2026-07-05T08:11:00Z"},{"alias_kind":"pith_short_16","alias_value":"FDXJ5VJ4CTO4GSOH","created_at":"2026-07-05T08:11:00Z"},{"alias_kind":"pith_short_8","alias_value":"FDXJ5VJ4","created_at":"2026-07-05T08:11:00Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:FDXJ5VJ4CTO4GSOHD7I6ULXFUE","target":"record","payload":{"canonical_record":{"source":{"id":"2401.16386","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-01-29T18:27:52Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"900d146919bf3b665f55cc988947032a2e0b9e19696c8b8e38e5cc0eccb6b282","abstract_canon_sha256":"829bb629172c729bd04077952c2f142261054ee6ac613d6dc9442ad2bfa2829b"},"schema_version":"1.0"},"canonical_sha256":"28ee9ed53c14ddc349c71fd1ea2ee5a13a11b4c1db017e888eced9d590d6f9e8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:11:00.979861Z","signature_b64":"dnr4HZS5+TZHucsdnzKWxIENuUONEfV1UWQQQy7eHQLXlrSiV1iDlL4ABG+VshdgHG6aNCKWfFiYKHv5g9QAAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"28ee9ed53c14ddc349c71fd1ea2ee5a13a11b4c1db017e888eced9d590d6f9e8","last_reissued_at":"2026-07-05T08:11:00.979299Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:11:00.979299Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2401.16386","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":"2026-07-05T08:11:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dvHvoZ5BjaCFcvrLgdpETiCOKC7nO83XPuxeySzLYHPWeZfUK7mQ8tCzRdpnDBE0yfFjNka8XPfRYMUKLxwbBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T04:27:43.840833Z"},"content_sha256":"bb806828b8fbf48176778b8a1de78a1c020fe35714dc467c81c86bf108f7e8e8","schema_version":"1.0","event_id":"sha256:bb806828b8fbf48176778b8a1de78a1c020fe35714dc467c81c86bf108f7e8e8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:FDXJ5VJ4CTO4GSOHD7I6ULXFUE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Continual Learning with Pre-Trained Models: A Survey","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.LG","authors_text":"Da-Wei Zhou, De-Chuan Zhan, Hai-Long Sun, Han-Jia Ye, Jingyi Ning","submitted_at":"2024-01-29T18:27:52Z","abstract_excerpt":"Nowadays, real-world applications often face streaming data, which requires the learning system to absorb new knowledge as data evolves. Continual Learning (CL) aims to achieve this goal and meanwhile overcome the catastrophic forgetting of former knowledge when learning new ones. Typical CL methods build the model from scratch to grow with incoming data. However, the advent of the pre-trained model (PTM) era has sparked immense research interest, particularly in leveraging PTMs' robust representational capabilities. This paper presents a comprehensive survey of the latest advancements in PTM-"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.16386","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/2401.16386/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":"2026-07-05T08:11:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"89IxIMnsk6wkxVWeey52OLt2ddaZOnXdUIKKrUMMFGnwGqJHMylNjbgVt0jRvrrxpbYGDHRIvuqDc4XqOrHnAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T04:27:43.841347Z"},"content_sha256":"92cb1447ea589897200b1dcb0e95c1bf0db20b97e3f51eb0235c21116f2a1263","schema_version":"1.0","event_id":"sha256:92cb1447ea589897200b1dcb0e95c1bf0db20b97e3f51eb0235c21116f2a1263"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FDXJ5VJ4CTO4GSOHD7I6ULXFUE/bundle.json","state_url":"https://pith.science/pith/FDXJ5VJ4CTO4GSOHD7I6ULXFUE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FDXJ5VJ4CTO4GSOHD7I6ULXFUE/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":"2026-08-19T04:27:43Z","links":{"resolver":"https://pith.science/pith/FDXJ5VJ4CTO4GSOHD7I6ULXFUE","bundle":"https://pith.science/pith/FDXJ5VJ4CTO4GSOHD7I6ULXFUE/bundle.json","state":"https://pith.science/pith/FDXJ5VJ4CTO4GSOHD7I6ULXFUE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FDXJ5VJ4CTO4GSOHD7I6ULXFUE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:FDXJ5VJ4CTO4GSOHD7I6ULXFUE","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":"829bb629172c729bd04077952c2f142261054ee6ac613d6dc9442ad2bfa2829b","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-01-29T18:27:52Z","title_canon_sha256":"900d146919bf3b665f55cc988947032a2e0b9e19696c8b8e38e5cc0eccb6b282"},"schema_version":"1.0","source":{"id":"2401.16386","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2401.16386","created_at":"2026-07-05T08:11:00Z"},{"alias_kind":"arxiv_version","alias_value":"2401.16386v2","created_at":"2026-07-05T08:11:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.16386","created_at":"2026-07-05T08:11:00Z"},{"alias_kind":"pith_short_12","alias_value":"FDXJ5VJ4CTO4","created_at":"2026-07-05T08:11:00Z"},{"alias_kind":"pith_short_16","alias_value":"FDXJ5VJ4CTO4GSOH","created_at":"2026-07-05T08:11:00Z"},{"alias_kind":"pith_short_8","alias_value":"FDXJ5VJ4","created_at":"2026-07-05T08:11:00Z"}],"graph_snapshots":[{"event_id":"sha256:92cb1447ea589897200b1dcb0e95c1bf0db20b97e3f51eb0235c21116f2a1263","target":"graph","created_at":"2026-07-05T08:11:00Z","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/2401.16386/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Nowadays, real-world applications often face streaming data, which requires the learning system to absorb new knowledge as data evolves. Continual Learning (CL) aims to achieve this goal and meanwhile overcome the catastrophic forgetting of former knowledge when learning new ones. Typical CL methods build the model from scratch to grow with incoming data. However, the advent of the pre-trained model (PTM) era has sparked immense research interest, particularly in leveraging PTMs' robust representational capabilities. This paper presents a comprehensive survey of the latest advancements in PTM-","authors_text":"Da-Wei Zhou, De-Chuan Zhan, Hai-Long Sun, Han-Jia Ye, Jingyi Ning","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-01-29T18:27:52Z","title":"Continual Learning with Pre-Trained Models: A Survey"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.16386","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:bb806828b8fbf48176778b8a1de78a1c020fe35714dc467c81c86bf108f7e8e8","target":"record","created_at":"2026-07-05T08:11:00Z","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":"829bb629172c729bd04077952c2f142261054ee6ac613d6dc9442ad2bfa2829b","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-01-29T18:27:52Z","title_canon_sha256":"900d146919bf3b665f55cc988947032a2e0b9e19696c8b8e38e5cc0eccb6b282"},"schema_version":"1.0","source":{"id":"2401.16386","kind":"arxiv","version":2}},"canonical_sha256":"28ee9ed53c14ddc349c71fd1ea2ee5a13a11b4c1db017e888eced9d590d6f9e8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"28ee9ed53c14ddc349c71fd1ea2ee5a13a11b4c1db017e888eced9d590d6f9e8","first_computed_at":"2026-07-05T08:11:00.979299Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:11:00.979299Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"dnr4HZS5+TZHucsdnzKWxIENuUONEfV1UWQQQy7eHQLXlrSiV1iDlL4ABG+VshdgHG6aNCKWfFiYKHv5g9QAAA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:11:00.979861Z","signed_message":"canonical_sha256_bytes"},"source_id":"2401.16386","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bb806828b8fbf48176778b8a1de78a1c020fe35714dc467c81c86bf108f7e8e8","sha256:92cb1447ea589897200b1dcb0e95c1bf0db20b97e3f51eb0235c21116f2a1263"],"state_sha256":"71cb4d1aec3a5718a0ca09ec1d9000f572788f2805b00d37b7aeb5067dc28ca2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PTxnS/k+aacZegeJIU6M2n+A2tQy3Sl5ETvYStdugiu75hGNSV2PRbydCzrIJpeaHWct+r6iWMb6aows48EfAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T04:27:43.847166Z","bundle_sha256":"0dd46fb4d584fd19acac3cf4e16289a11c79d9a718614f615eaa023360fb95a3"}}