{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:4Y5T7HBXY53WC477TZ7OKUV2YF","short_pith_number":"pith:4Y5T7HBX","schema_version":"1.0","canonical_sha256":"e63b3f9c37c7776173ff9e7ee552bac146f2deb7e7148eabfb037528e501d628","source":{"kind":"arxiv","id":"2303.06686","version":1},"attestation_state":"computed","paper":{"title":"MizAR 60 for Mizar 50","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.LO","cs.SC"],"primary_cat":"cs.AI","authors_text":"Bartosz Piotrowski, Cezary Kaliszyk, Jan Jakub\\r{u}v, Josef Urban, Karel Chvalovsk\\'y, Martin Suda, Mirek Ol\\v{s}\\'ak, Stephan Schulz, Zarathustra Goertzel","submitted_at":"2023-03-12T15:13:05Z","abstract_excerpt":"As a present to Mizar on its 50th anniversary, we develop an AI/TP system that automatically proves about 60\\% of the Mizar theorems in the hammer setting. We also automatically prove 75\\% of the Mizar theorems when the automated provers are helped by using only the premises used in the human-written Mizar proofs. We describe the methods and large-scale experiments leading to these results. This includes in particular the E and Vampire provers, their ENIGMA and Deepire learning modifications, a number of learning-based premise selection methods, and the incremental loop that interleaves growin"},"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":"2303.06686","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2023-03-12T15:13:05Z","cross_cats_sorted":["cs.LG","cs.LO","cs.SC"],"title_canon_sha256":"5e11bca9e6e484443281a1e59bf94016778b5908cab59525385fb1dc4fb74f19","abstract_canon_sha256":"cb8bcb4ff5d989632989347c139619e189d30bd5226ae345fb41ac139f290a34"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:50:21.887115Z","signature_b64":"n2ngEoqiupmrW7ka0r/NpeNygW3LFjysaNRxGSCc36oyP9g525s8XifUldHyXK2Emvi57Rq94gM8FR3hImN0Cw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e63b3f9c37c7776173ff9e7ee552bac146f2deb7e7148eabfb037528e501d628","last_reissued_at":"2026-07-05T05:50:21.886738Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:50:21.886738Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"MizAR 60 for Mizar 50","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.LO","cs.SC"],"primary_cat":"cs.AI","authors_text":"Bartosz Piotrowski, Cezary Kaliszyk, Jan Jakub\\r{u}v, Josef Urban, Karel Chvalovsk\\'y, Martin Suda, Mirek Ol\\v{s}\\'ak, Stephan Schulz, Zarathustra Goertzel","submitted_at":"2023-03-12T15:13:05Z","abstract_excerpt":"As a present to Mizar on its 50th anniversary, we develop an AI/TP system that automatically proves about 60\\% of the Mizar theorems in the hammer setting. We also automatically prove 75\\% of the Mizar theorems when the automated provers are helped by using only the premises used in the human-written Mizar proofs. We describe the methods and large-scale experiments leading to these results. This includes in particular the E and Vampire provers, their ENIGMA and Deepire learning modifications, a number of learning-based premise selection methods, and the incremental loop that interleaves growin"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.06686","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/2303.06686/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":"2303.06686","created_at":"2026-07-05T05:50:21.886800+00:00"},{"alias_kind":"arxiv_version","alias_value":"2303.06686v1","created_at":"2026-07-05T05:50:21.886800+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.06686","created_at":"2026-07-05T05:50:21.886800+00:00"},{"alias_kind":"pith_short_12","alias_value":"4Y5T7HBXY53W","created_at":"2026-07-05T05:50:21.886800+00:00"},{"alias_kind":"pith_short_16","alias_value":"4Y5T7HBXY53WC477","created_at":"2026-07-05T05:50:21.886800+00:00"},{"alias_kind":"pith_short_8","alias_value":"4Y5T7HBX","created_at":"2026-07-05T05:50:21.886800+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/4Y5T7HBXY53WC477TZ7OKUV2YF","json":"https://pith.science/pith/4Y5T7HBXY53WC477TZ7OKUV2YF.json","graph_json":"https://pith.science/api/pith-number/4Y5T7HBXY53WC477TZ7OKUV2YF/graph.json","events_json":"https://pith.science/api/pith-number/4Y5T7HBXY53WC477TZ7OKUV2YF/events.json","paper":"https://pith.science/paper/4Y5T7HBX"},"agent_actions":{"view_html":"https://pith.science/pith/4Y5T7HBXY53WC477TZ7OKUV2YF","download_json":"https://pith.science/pith/4Y5T7HBXY53WC477TZ7OKUV2YF.json","view_paper":"https://pith.science/paper/4Y5T7HBX","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2303.06686&json=true","fetch_graph":"https://pith.science/api/pith-number/4Y5T7HBXY53WC477TZ7OKUV2YF/graph.json","fetch_events":"https://pith.science/api/pith-number/4Y5T7HBXY53WC477TZ7OKUV2YF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/4Y5T7HBXY53WC477TZ7OKUV2YF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/4Y5T7HBXY53WC477TZ7OKUV2YF/action/storage_attestation","attest_author":"https://pith.science/pith/4Y5T7HBXY53WC477TZ7OKUV2YF/action/author_attestation","sign_citation":"https://pith.science/pith/4Y5T7HBXY53WC477TZ7OKUV2YF/action/citation_signature","submit_replication":"https://pith.science/pith/4Y5T7HBXY53WC477TZ7OKUV2YF/action/replication_record"}},"created_at":"2026-07-05T05:50:21.886800+00:00","updated_at":"2026-07-05T05:50:21.886800+00:00"}