{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:T33MDQD4NVUVFLLA2C5FWQHXY4","short_pith_number":"pith:T33MDQD4","schema_version":"1.0","canonical_sha256":"9ef6c1c07c6d6952ad60d0ba5b40f7c7343c2c31e177972ebef0d16f4a9ac539","source":{"kind":"arxiv","id":"2606.08447","version":1},"attestation_state":"computed","paper":{"title":"Not Just After One: Sleep-Inspired Replay Prevents Catastrophic Forgetting After Sequential Tasks","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Anthony Bazhenov, Giri P. Krishnan, Jean Erik Delanois","submitted_at":"2026-06-07T04:27:54Z","abstract_excerpt":"One of the critical limitations of artificial neural networks is their lack of ability to continually learn: training on new tasks often leads to interference and forgetting of the previous ones. While several algorithms have been proposed to protect old memories from interference, they are typically applied during or immediately after each new episode of training. In contrast, humans and animals can learn continuously, acquiring multiple new memories during active learning before consolidating all of them into long-term storage. Here we show that multiple new tasks can be trained sequentially"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2606.08447","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-07T04:27:54Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"b35498c1c3b7ef221dbcf1fa3af3db54a66012c51eb475fcad0e628e49f5cf44","abstract_canon_sha256":"399af98254f307b4fdf5a9cf9002082c3b6f4080b5f404cce54a41b04d8fcb5e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-09T01:05:36.887720Z","signature_b64":"I2eJ/Ds5sehswS0P0J4b2rEo6hzWsNOsH63Kd8DlT4oqCFNa3IIAkiJzdmUWKuFg6gRh1YsRPUuYe+spQjy0AA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9ef6c1c07c6d6952ad60d0ba5b40f7c7343c2c31e177972ebef0d16f4a9ac539","last_reissued_at":"2026-06-09T01:05:36.887346Z","signature_status":"signed_v1","first_computed_at":"2026-06-09T01:05:36.887346Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Not Just After One: Sleep-Inspired Replay Prevents Catastrophic Forgetting After Sequential Tasks","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Anthony Bazhenov, Giri P. Krishnan, Jean Erik Delanois","submitted_at":"2026-06-07T04:27:54Z","abstract_excerpt":"One of the critical limitations of artificial neural networks is their lack of ability to continually learn: training on new tasks often leads to interference and forgetting of the previous ones. While several algorithms have been proposed to protect old memories from interference, they are typically applied during or immediately after each new episode of training. In contrast, humans and animals can learn continuously, acquiring multiple new memories during active learning before consolidating all of them into long-term storage. Here we show that multiple new tasks can be trained sequentially"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.08447","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/2606.08447/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2606.08447","created_at":"2026-06-09T01:05:36.887404+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.08447v1","created_at":"2026-06-09T01:05:36.887404+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.08447","created_at":"2026-06-09T01:05:36.887404+00:00"},{"alias_kind":"pith_short_12","alias_value":"T33MDQD4NVUV","created_at":"2026-06-09T01:05:36.887404+00:00"},{"alias_kind":"pith_short_16","alias_value":"T33MDQD4NVUVFLLA","created_at":"2026-06-09T01:05:36.887404+00:00"},{"alias_kind":"pith_short_8","alias_value":"T33MDQD4","created_at":"2026-06-09T01:05:36.887404+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/T33MDQD4NVUVFLLA2C5FWQHXY4","json":"https://pith.science/pith/T33MDQD4NVUVFLLA2C5FWQHXY4.json","graph_json":"https://pith.science/api/pith-number/T33MDQD4NVUVFLLA2C5FWQHXY4/graph.json","events_json":"https://pith.science/api/pith-number/T33MDQD4NVUVFLLA2C5FWQHXY4/events.json","paper":"https://pith.science/paper/T33MDQD4"},"agent_actions":{"view_html":"https://pith.science/pith/T33MDQD4NVUVFLLA2C5FWQHXY4","download_json":"https://pith.science/pith/T33MDQD4NVUVFLLA2C5FWQHXY4.json","view_paper":"https://pith.science/paper/T33MDQD4","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.08447&json=true","fetch_graph":"https://pith.science/api/pith-number/T33MDQD4NVUVFLLA2C5FWQHXY4/graph.json","fetch_events":"https://pith.science/api/pith-number/T33MDQD4NVUVFLLA2C5FWQHXY4/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/T33MDQD4NVUVFLLA2C5FWQHXY4/action/timestamp_anchor","attest_storage":"https://pith.science/pith/T33MDQD4NVUVFLLA2C5FWQHXY4/action/storage_attestation","attest_author":"https://pith.science/pith/T33MDQD4NVUVFLLA2C5FWQHXY4/action/author_attestation","sign_citation":"https://pith.science/pith/T33MDQD4NVUVFLLA2C5FWQHXY4/action/citation_signature","submit_replication":"https://pith.science/pith/T33MDQD4NVUVFLLA2C5FWQHXY4/action/replication_record"}},"created_at":"2026-06-09T01:05:36.887404+00:00","updated_at":"2026-06-09T01:05:36.887404+00:00"}