{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:5NIRUFXP3X4RDY7XD7ZDFPRG7L","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":"7d4ca3f9f29e8dc9d6bf733e76f1572b1bdf794a639ab407cd49d39dd149577f","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-06-26T14:53:34Z","title_canon_sha256":"1bfdc09eee423d23337d391934aaf767f0e53cdea32f40d01f5120d3dfcefbff"},"schema_version":"1.0","source":{"id":"1706.08840","kind":"arxiv","version":6}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1706.08840","created_at":"2026-07-05T04:56:57Z"},{"alias_kind":"arxiv_version","alias_value":"1706.08840v6","created_at":"2026-07-05T04:56:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1706.08840","created_at":"2026-07-05T04:56:57Z"},{"alias_kind":"pith_short_12","alias_value":"5NIRUFXP3X4R","created_at":"2026-07-05T04:56:57Z"},{"alias_kind":"pith_short_16","alias_value":"5NIRUFXP3X4RDY7X","created_at":"2026-07-05T04:56:57Z"},{"alias_kind":"pith_short_8","alias_value":"5NIRUFXP","created_at":"2026-07-05T04:56:57Z"}],"graph_snapshots":[{"event_id":"sha256:dbae958d4ae0e87c3f6f04e4e4035d5eada450f78781a06a9b6b9feedb09545e","target":"graph","created_at":"2026-07-05T04:56:57Z","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/1706.08840/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"One major obstacle towards AI is the poor ability of models to solve new problems quicker, and without forgetting previously acquired knowledge. To better understand this issue, we study the problem of continual learning, where the model observes, once and one by one, examples concerning a sequence of tasks. First, we propose a set of metrics to evaluate models learning over a continuum of data. These metrics characterize models not only by their test accuracy, but also in terms of their ability to transfer knowledge across tasks. Second, we propose a model for continual learning, called Gradi","authors_text":"David Lopez-Paz, Marc'Aurelio Ranzato","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-06-26T14:53:34Z","title":"Gradient Episodic Memory for Continual Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1706.08840","kind":"arxiv","version":6},"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":"sha256:5f5429cfb89211e0b11b37875a8c72e670548ea6a7d0f3d4e20eef6aab1df068","target":"record","created_at":"2026-07-05T04:56:57Z","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":"7d4ca3f9f29e8dc9d6bf733e76f1572b1bdf794a639ab407cd49d39dd149577f","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-06-26T14:53:34Z","title_canon_sha256":"1bfdc09eee423d23337d391934aaf767f0e53cdea32f40d01f5120d3dfcefbff"},"schema_version":"1.0","source":{"id":"1706.08840","kind":"arxiv","version":6}},"canonical_sha256":"eb511a16efddf911e3f71ff232be26fafc32c062d79cdb93a7933048f8e649e8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"eb511a16efddf911e3f71ff232be26fafc32c062d79cdb93a7933048f8e649e8","first_computed_at":"2026-07-05T04:56:57.442380Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:56:57.442380Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ebFnXCvmbU1KPj0wcjcegllaMlt0Tqy6Mx5M3aeZVjqRzsC19m9D/jWF+1yCoo8ehVDb3xC7jKF19Z6h3YQtAA==","signature_status":"signed_v1","signed_at":"2026-07-05T04:56:57.442849Z","signed_message":"canonical_sha256_bytes"},"source_id":"1706.08840","source_kind":"arxiv","source_version":6}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5f5429cfb89211e0b11b37875a8c72e670548ea6a7d0f3d4e20eef6aab1df068","sha256:dbae958d4ae0e87c3f6f04e4e4035d5eada450f78781a06a9b6b9feedb09545e"],"state_sha256":"d0912e87397716f90595622b7a5b0f1ebca29e4ce0a2b35a9e7f1580c1733548"}