{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:7GBMROZCESA3KLPC23HVOLXLD5","short_pith_number":"pith:7GBMROZC","schema_version":"1.0","canonical_sha256":"f982c8bb222481b52de2d6cf572eeb1f462db33eb38d53b9d538998e22e875db","source":{"kind":"arxiv","id":"1611.08733","version":1},"attestation_state":"computed","paper":{"title":"BliStrTune: Hierarchical Invention of Theorem Proving Strategies","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.LO","authors_text":"Jan Jakubuv, Josef Urban","submitted_at":"2016-11-26T18:48:43Z","abstract_excerpt":"Inventing targeted proof search strategies for specific problem sets is a difficult task. State-of-the-art automated theorem provers (ATPs) such as E allow a large number of user-specified proof search strategies described in a rich domain specific language. Several machine learning methods that invent strategies automatically for ATPs were proposed previously. One of them is the Blind Strategymaker (BliStr), a system for automated invention of ATP strategies.\n  In this paper we introduce BliStrTune -- a hierarchical extension of BliStr. BliStrTune allows exploring much larger space of E strat"},"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":"1611.08733","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LO","submitted_at":"2016-11-26T18:48:43Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"d9e54e00cad5218815cd67b2c4e2a4ebe6158f9813abfe6ea7a1088b10f7af35","abstract_canon_sha256":"0a945ee4d821c795915b2a529b06d3dbab4c8f38722d49a87578a573dc0841a8"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:52:13.697377Z","signature_b64":"AVZtyt3QYL2NbjDokRlWKdn6BpNyZAvxsT3KE5AZHVTnIcOVDxjruUCH8TqG44dVjoF8msdggV3yxFPgtEV8BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f982c8bb222481b52de2d6cf572eeb1f462db33eb38d53b9d538998e22e875db","last_reissued_at":"2026-05-18T00:52:13.696625Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:52:13.696625Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"BliStrTune: Hierarchical Invention of Theorem Proving Strategies","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.LO","authors_text":"Jan Jakubuv, Josef Urban","submitted_at":"2016-11-26T18:48:43Z","abstract_excerpt":"Inventing targeted proof search strategies for specific problem sets is a difficult task. State-of-the-art automated theorem provers (ATPs) such as E allow a large number of user-specified proof search strategies described in a rich domain specific language. Several machine learning methods that invent strategies automatically for ATPs were proposed previously. One of them is the Blind Strategymaker (BliStr), a system for automated invention of ATP strategies.\n  In this paper we introduce BliStrTune -- a hierarchical extension of BliStr. BliStrTune allows exploring much larger space of E strat"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1611.08733","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":""},"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":"1611.08733","created_at":"2026-05-18T00:52:13.696735+00:00"},{"alias_kind":"arxiv_version","alias_value":"1611.08733v1","created_at":"2026-05-18T00:52:13.696735+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1611.08733","created_at":"2026-05-18T00:52:13.696735+00:00"},{"alias_kind":"pith_short_12","alias_value":"7GBMROZCESA3","created_at":"2026-05-18T12:30:04.600751+00:00"},{"alias_kind":"pith_short_16","alias_value":"7GBMROZCESA3KLPC","created_at":"2026-05-18T12:30:04.600751+00:00"},{"alias_kind":"pith_short_8","alias_value":"7GBMROZC","created_at":"2026-05-18T12:30:04.600751+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/7GBMROZCESA3KLPC23HVOLXLD5","json":"https://pith.science/pith/7GBMROZCESA3KLPC23HVOLXLD5.json","graph_json":"https://pith.science/api/pith-number/7GBMROZCESA3KLPC23HVOLXLD5/graph.json","events_json":"https://pith.science/api/pith-number/7GBMROZCESA3KLPC23HVOLXLD5/events.json","paper":"https://pith.science/paper/7GBMROZC"},"agent_actions":{"view_html":"https://pith.science/pith/7GBMROZCESA3KLPC23HVOLXLD5","download_json":"https://pith.science/pith/7GBMROZCESA3KLPC23HVOLXLD5.json","view_paper":"https://pith.science/paper/7GBMROZC","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1611.08733&json=true","fetch_graph":"https://pith.science/api/pith-number/7GBMROZCESA3KLPC23HVOLXLD5/graph.json","fetch_events":"https://pith.science/api/pith-number/7GBMROZCESA3KLPC23HVOLXLD5/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/7GBMROZCESA3KLPC23HVOLXLD5/action/timestamp_anchor","attest_storage":"https://pith.science/pith/7GBMROZCESA3KLPC23HVOLXLD5/action/storage_attestation","attest_author":"https://pith.science/pith/7GBMROZCESA3KLPC23HVOLXLD5/action/author_attestation","sign_citation":"https://pith.science/pith/7GBMROZCESA3KLPC23HVOLXLD5/action/citation_signature","submit_replication":"https://pith.science/pith/7GBMROZCESA3KLPC23HVOLXLD5/action/replication_record"}},"created_at":"2026-05-18T00:52:13.696735+00:00","updated_at":"2026-05-18T00:52:13.696735+00:00"}