{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:3KIVPWZNU642B66AIUOPYX7AWQ","short_pith_number":"pith:3KIVPWZN","canonical_record":{"source":{"id":"2303.10455","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-03-18T16:45:54Z","cross_cats_sorted":["cs.AI","cs.CV"],"title_canon_sha256":"33b630c7797431a887c910703be1dec3d27585cb0a0e41d560e6fa859a606fd6","abstract_canon_sha256":"c3d11803f6643ea6957d8bdfa817cb5909adfe2c483b3d04d36026c427bc535f"},"schema_version":"1.0"},"canonical_sha256":"da9157db2da7b9a0fbc0451cfc5fe0b40fd36b1868a1ad656601f0464958059b","source":{"kind":"arxiv","id":"2303.10455","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2303.10455","created_at":"2026-07-05T05:52:32Z"},{"alias_kind":"arxiv_version","alias_value":"2303.10455v1","created_at":"2026-07-05T05:52:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.10455","created_at":"2026-07-05T05:52:32Z"},{"alias_kind":"pith_short_12","alias_value":"3KIVPWZNU642","created_at":"2026-07-05T05:52:32Z"},{"alias_kind":"pith_short_16","alias_value":"3KIVPWZNU642B66A","created_at":"2026-07-05T05:52:32Z"},{"alias_kind":"pith_short_8","alias_value":"3KIVPWZN","created_at":"2026-07-05T05:52:32Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:3KIVPWZNU642B66AIUOPYX7AWQ","target":"record","payload":{"canonical_record":{"source":{"id":"2303.10455","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-03-18T16:45:54Z","cross_cats_sorted":["cs.AI","cs.CV"],"title_canon_sha256":"33b630c7797431a887c910703be1dec3d27585cb0a0e41d560e6fa859a606fd6","abstract_canon_sha256":"c3d11803f6643ea6957d8bdfa817cb5909adfe2c483b3d04d36026c427bc535f"},"schema_version":"1.0"},"canonical_sha256":"da9157db2da7b9a0fbc0451cfc5fe0b40fd36b1868a1ad656601f0464958059b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:52:32.529185Z","signature_b64":"lRl/TCVNbNoPjt1uOoPTQNeNPuUYevPk/rP9TTjEBQz0FhvY2i7e5gs7+zTZox3nVAh/gNffM3TBKnuj5UCACg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"da9157db2da7b9a0fbc0451cfc5fe0b40fd36b1868a1ad656601f0464958059b","last_reissued_at":"2026-07-05T05:52:32.528840Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:52:32.528840Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2303.10455","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":"2026-07-05T05:52:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Y/L9BuQ1bIsqpSZ9FhFrYCH8VDkp/PAeCoakUD+VCxtakDW72TzzNNPJjYuDF2WowM3dmxWCKO9Gj4kXdWkRCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T11:41:23.673919Z"},"content_sha256":"098cf0499c6a3dd075a983b56c48ccd4c531f20a01a7799d1cfada60b2143e42","schema_version":"1.0","event_id":"sha256:098cf0499c6a3dd075a983b56c48ccd4c531f20a01a7799d1cfada60b2143e42"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:3KIVPWZNU642B66AIUOPYX7AWQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Learn, Unlearn and Relearn: An Online Learning Paradigm for Deep Neural Networks","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.AI","cs.CV"],"primary_cat":"cs.LG","authors_text":"Bahram Zonooz, Elahe Arani, Vijaya Raghavan T. Ramkumar","submitted_at":"2023-03-18T16:45:54Z","abstract_excerpt":"Deep neural networks (DNNs) are often trained on the premise that the complete training data set is provided ahead of time. However, in real-world scenarios, data often arrive in chunks over time. This leads to important considerations about the optimal strategy for training DNNs, such as whether to fine-tune them with each chunk of incoming data (warm-start) or to retrain them from scratch with the entire corpus of data whenever a new chunk is available. While employing the latter for training can be resource-intensive, recent work has pointed out the lack of generalization in warm-start mode"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.10455","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/2303.10455/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":"2026-07-05T05:52:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9fRxgAo+hwOkCRYz4fA6zBUPyjhwwIUfiAaBiO8pmJVKRvkYKMgVPd6DVe2it7K8ESwIjVD8v4CddyfWJ0pXBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T11:41:23.674411Z"},"content_sha256":"a53db2259cd60c11940d1bdd5d0c042e0f3f2df638dcaa773d20ad45e51ca9f5","schema_version":"1.0","event_id":"sha256:a53db2259cd60c11940d1bdd5d0c042e0f3f2df638dcaa773d20ad45e51ca9f5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3KIVPWZNU642B66AIUOPYX7AWQ/bundle.json","state_url":"https://pith.science/pith/3KIVPWZNU642B66AIUOPYX7AWQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3KIVPWZNU642B66AIUOPYX7AWQ/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":"2026-08-09T11:41:23Z","links":{"resolver":"https://pith.science/pith/3KIVPWZNU642B66AIUOPYX7AWQ","bundle":"https://pith.science/pith/3KIVPWZNU642B66AIUOPYX7AWQ/bundle.json","state":"https://pith.science/pith/3KIVPWZNU642B66AIUOPYX7AWQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3KIVPWZNU642B66AIUOPYX7AWQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:3KIVPWZNU642B66AIUOPYX7AWQ","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":"c3d11803f6643ea6957d8bdfa817cb5909adfe2c483b3d04d36026c427bc535f","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-03-18T16:45:54Z","title_canon_sha256":"33b630c7797431a887c910703be1dec3d27585cb0a0e41d560e6fa859a606fd6"},"schema_version":"1.0","source":{"id":"2303.10455","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2303.10455","created_at":"2026-07-05T05:52:32Z"},{"alias_kind":"arxiv_version","alias_value":"2303.10455v1","created_at":"2026-07-05T05:52:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.10455","created_at":"2026-07-05T05:52:32Z"},{"alias_kind":"pith_short_12","alias_value":"3KIVPWZNU642","created_at":"2026-07-05T05:52:32Z"},{"alias_kind":"pith_short_16","alias_value":"3KIVPWZNU642B66A","created_at":"2026-07-05T05:52:32Z"},{"alias_kind":"pith_short_8","alias_value":"3KIVPWZN","created_at":"2026-07-05T05:52:32Z"}],"graph_snapshots":[{"event_id":"sha256:a53db2259cd60c11940d1bdd5d0c042e0f3f2df638dcaa773d20ad45e51ca9f5","target":"graph","created_at":"2026-07-05T05:52:32Z","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/2303.10455/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep neural networks (DNNs) are often trained on the premise that the complete training data set is provided ahead of time. However, in real-world scenarios, data often arrive in chunks over time. This leads to important considerations about the optimal strategy for training DNNs, such as whether to fine-tune them with each chunk of incoming data (warm-start) or to retrain them from scratch with the entire corpus of data whenever a new chunk is available. While employing the latter for training can be resource-intensive, recent work has pointed out the lack of generalization in warm-start mode","authors_text":"Bahram Zonooz, Elahe Arani, Vijaya Raghavan T. Ramkumar","cross_cats":["cs.AI","cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-03-18T16:45:54Z","title":"Learn, Unlearn and Relearn: An Online Learning Paradigm for Deep Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.10455","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":"sha256:098cf0499c6a3dd075a983b56c48ccd4c531f20a01a7799d1cfada60b2143e42","target":"record","created_at":"2026-07-05T05:52:32Z","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":"c3d11803f6643ea6957d8bdfa817cb5909adfe2c483b3d04d36026c427bc535f","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-03-18T16:45:54Z","title_canon_sha256":"33b630c7797431a887c910703be1dec3d27585cb0a0e41d560e6fa859a606fd6"},"schema_version":"1.0","source":{"id":"2303.10455","kind":"arxiv","version":1}},"canonical_sha256":"da9157db2da7b9a0fbc0451cfc5fe0b40fd36b1868a1ad656601f0464958059b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"da9157db2da7b9a0fbc0451cfc5fe0b40fd36b1868a1ad656601f0464958059b","first_computed_at":"2026-07-05T05:52:32.528840Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:52:32.528840Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"lRl/TCVNbNoPjt1uOoPTQNeNPuUYevPk/rP9TTjEBQz0FhvY2i7e5gs7+zTZox3nVAh/gNffM3TBKnuj5UCACg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:52:32.529185Z","signed_message":"canonical_sha256_bytes"},"source_id":"2303.10455","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:098cf0499c6a3dd075a983b56c48ccd4c531f20a01a7799d1cfada60b2143e42","sha256:a53db2259cd60c11940d1bdd5d0c042e0f3f2df638dcaa773d20ad45e51ca9f5"],"state_sha256":"f34bb2e3e693a0adf0ed81ab39b8060010d041ed3ba42978f9cf99dc6974bf2e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"P7LoCK5IdPu3JDc2WVL6zyKkdmUfU7Af90MbEiB11GjuhhX/RlhvlNnRUuI1Mmvtl4JZcngRRkPEEkEfFzb+Dg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T11:41:23.677717Z","bundle_sha256":"8012b977dad6b0339e07d8cdff620b1a22904e4554e919f979a7ae839a8ed09c"}}