{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:RPPM2D7CY4CFSDFK3V4BOYFGEU","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":"d89c005b9bf97fac850b4515b29d50481807c85a229c980d56f3461073d4af39","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2020-06-15T13:06:29Z","title_canon_sha256":"87fc59f6f4220174f1008935366c8b0a664f8cb26228105c9e0f8a556d3879d4"},"schema_version":"1.0","source":{"id":"2006.08381","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2006.08381","created_at":"2026-07-05T01:10:20Z"},{"alias_kind":"arxiv_version","alias_value":"2006.08381v1","created_at":"2026-07-05T01:10:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2006.08381","created_at":"2026-07-05T01:10:20Z"},{"alias_kind":"pith_short_12","alias_value":"RPPM2D7CY4CF","created_at":"2026-07-05T01:10:20Z"},{"alias_kind":"pith_short_16","alias_value":"RPPM2D7CY4CFSDFK","created_at":"2026-07-05T01:10:20Z"},{"alias_kind":"pith_short_8","alias_value":"RPPM2D7C","created_at":"2026-07-05T01:10:20Z"}],"graph_snapshots":[{"event_id":"sha256:652a00a3cd86c7db48c9cb35958760f5930337422c31bff0adc8e6b3188068a5","target":"graph","created_at":"2026-07-05T01:10:20Z","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/2006.08381/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Expert problem-solving is driven by powerful languages for thinking about problems and their solutions. Acquiring expertise means learning these languages -- systems of concepts, alongside the skills to use them. We present DreamCoder, a system that learns to solve problems by writing programs. It builds expertise by creating programming languages for expressing domain concepts, together with neural networks to guide the search for programs within these languages. A ``wake-sleep'' learning algorithm alternately extends the language with new symbolic abstractions and trains the neural network o","authors_text":"Armando Solar-Lezama, Catherine Wong, Joshua B. Tenenbaum, Kevin Ellis, Lucas Morales, Luc Cary, Luke Hewitt, Mathias Sable-Meyer, Maxwell Nye","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2020-06-15T13:06:29Z","title":"DreamCoder: Growing generalizable, interpretable knowledge with wake-sleep Bayesian program learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2006.08381","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":"sha256:8f51ef7e37bf956f554469b46390ceca9a199d11b62569c9dd58a2426ea6488f","target":"record","created_at":"2026-07-05T01:10:20Z","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":"d89c005b9bf97fac850b4515b29d50481807c85a229c980d56f3461073d4af39","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2020-06-15T13:06:29Z","title_canon_sha256":"87fc59f6f4220174f1008935366c8b0a664f8cb26228105c9e0f8a556d3879d4"},"schema_version":"1.0","source":{"id":"2006.08381","kind":"arxiv","version":1}},"canonical_sha256":"8bdecd0fe2c704590caadd781760a6250288c75ee473d8fab0a933bc91032245","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8bdecd0fe2c704590caadd781760a6250288c75ee473d8fab0a933bc91032245","first_computed_at":"2026-07-05T01:10:20.984660Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:10:20.984660Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"13VNK55gHuOMc4EDaSa1AtPIzZ+uIRprrSdYPutIwYF1jYFy1u5vPQDk8mRbAwb4qwNj8KxHB3oW7KyZbW2YCw==","signature_status":"signed_v1","signed_at":"2026-07-05T01:10:20.985228Z","signed_message":"canonical_sha256_bytes"},"source_id":"2006.08381","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8f51ef7e37bf956f554469b46390ceca9a199d11b62569c9dd58a2426ea6488f","sha256:652a00a3cd86c7db48c9cb35958760f5930337422c31bff0adc8e6b3188068a5"],"state_sha256":"a2bdd017175fa66be55577b7947c1810960039cae7a77799856e6841c3dd9f0a"}