{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:WBW2RF2FHW6GGUWHINE5QSGY2N","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":"41fb3cdb6eaaf3935c5fde1de5ea50e5576c05000540474b7da2fa0b2c123234","cross_cats_sorted":["cs.CV","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-05-31T08:11:12Z","title_canon_sha256":"9112af5e15536b6de0239bcdcb2321157b39a4343e4340306e118c6322a71035"},"schema_version":"1.0","source":{"id":"1805.12369","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.12369","created_at":"2026-05-18T00:14:30Z"},{"alias_kind":"arxiv_version","alias_value":"1805.12369v1","created_at":"2026-05-18T00:14:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.12369","created_at":"2026-05-18T00:14:30Z"},{"alias_kind":"pith_short_12","alias_value":"WBW2RF2FHW6G","created_at":"2026-05-18T12:32:59Z"},{"alias_kind":"pith_short_16","alias_value":"WBW2RF2FHW6GGUWH","created_at":"2026-05-18T12:32:59Z"},{"alias_kind":"pith_short_8","alias_value":"WBW2RF2F","created_at":"2026-05-18T12:32:59Z"}],"graph_snapshots":[{"event_id":"sha256:4754c4bd4bc62c9185bb8ac156c5bc52532c5894ea1142fbe94ea94ed5099013","target":"graph","created_at":"2026-05-18T00:14:30Z","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"},"paper":{"abstract_excerpt":"Most artificial intelligence models have limiting ability to solve new tasks faster, without forgetting previously acquired knowledge. The recently emerging paradigm of continual learning aims to solve this issue, in which the model learns various tasks in a sequential fashion. In this work, a novel approach for continual learning is proposed, which searches for the best neural architecture for each coming task via sophisticatedly designed reinforcement learning strategies. We name it as Reinforced Continual Learning. Our method not only has good performance on preventing catastrophic forgetti","authors_text":"Ju Xu, Zhanxing Zhu","cross_cats":["cs.CV","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-05-31T08:11:12Z","title":"Reinforced Continual Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.12369","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:a8e4353eda7c349b433dfe82ecabcbe97c0adddf49321add1321748ca8658987","target":"record","created_at":"2026-05-18T00:14:30Z","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":"41fb3cdb6eaaf3935c5fde1de5ea50e5576c05000540474b7da2fa0b2c123234","cross_cats_sorted":["cs.CV","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-05-31T08:11:12Z","title_canon_sha256":"9112af5e15536b6de0239bcdcb2321157b39a4343e4340306e118c6322a71035"},"schema_version":"1.0","source":{"id":"1805.12369","kind":"arxiv","version":1}},"canonical_sha256":"b06da897453dbc6352c74349d848d8d36b4386e497115b7437f88c0576fba36f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b06da897453dbc6352c74349d848d8d36b4386e497115b7437f88c0576fba36f","first_computed_at":"2026-05-18T00:14:30.464596Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:14:30.464596Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"HSvaDVlETpyp4fTmh5xGNuJG03aFbLNqcBUocc4AnQH5b89glSFog/4ExRuZGSLOXsVgQlPQIvrUvdQ74PUbBg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:14:30.465279Z","signed_message":"canonical_sha256_bytes"},"source_id":"1805.12369","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a8e4353eda7c349b433dfe82ecabcbe97c0adddf49321add1321748ca8658987","sha256:4754c4bd4bc62c9185bb8ac156c5bc52532c5894ea1142fbe94ea94ed5099013"],"state_sha256":"5c46b4336a8f894c1de7db3acaa3751fc0ca768a42f586ebd5776998ff986792"}