{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:OSPULDQRQAGJJN3MCAKGJM4EI7","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":"eada50f0134d8be82e0b8dad3d4a13dad62ceebc9cab6bb447820032b7386956","cross_cats_sorted":["cs.LO","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2018-02-09T18:29:26Z","title_canon_sha256":"38c2bda7f9294010cf918d7d51dcf63b5c55b61c46a9259792588cf30d57cb3c"},"schema_version":"1.0","source":{"id":"1802.03375","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.03375","created_at":"2026-05-18T00:23:57Z"},{"alias_kind":"arxiv_version","alias_value":"1802.03375v1","created_at":"2026-05-18T00:23:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.03375","created_at":"2026-05-18T00:23:57Z"},{"alias_kind":"pith_short_12","alias_value":"OSPULDQRQAGJ","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_16","alias_value":"OSPULDQRQAGJJN3M","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_8","alias_value":"OSPULDQR","created_at":"2026-05-18T12:32:43Z"}],"graph_snapshots":[{"event_id":"sha256:a1af0186437ce88f78fec8a901fd9212a01b6a2f7cb410954f3a698ae1398db4","target":"graph","created_at":"2026-05-18T00:23:57Z","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"},"paper":{"abstract_excerpt":"ATPboost is a system for solving sets of large-theory problems by interleaving ATP runs with state-of-the-art machine learning of premise selection from the proofs. Unlike many previous approaches that use multi-label setting, the learning is implemented as binary classification that estimates the pairwise-relevance of (theorem, premise) pairs. ATPboost uses for this the XGBoost gradient boosting algorithm, which is fast and has state-of-the-art performance on many tasks. Learning in the binary setting however requires negative examples, which is nontrivial due to many alternative proofs. We d","authors_text":"Bartosz Piotrowski, Josef Urban","cross_cats":["cs.LO","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2018-02-09T18:29:26Z","title":"ATPboost: Learning Premise Selection in Binary Setting with ATP Feedback"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.03375","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":"sha256:09de77a04b836a8a79679b82df50a8d3c256bbae201d30c7abe919ed2c5344d6","target":"record","created_at":"2026-05-18T00:23:57Z","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":"eada50f0134d8be82e0b8dad3d4a13dad62ceebc9cab6bb447820032b7386956","cross_cats_sorted":["cs.LO","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2018-02-09T18:29:26Z","title_canon_sha256":"38c2bda7f9294010cf918d7d51dcf63b5c55b61c46a9259792588cf30d57cb3c"},"schema_version":"1.0","source":{"id":"1802.03375","kind":"arxiv","version":1}},"canonical_sha256":"749f458e11800c94b76c101464b38447c051ba83454914cf9cc2a14b1d31c75f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"749f458e11800c94b76c101464b38447c051ba83454914cf9cc2a14b1d31c75f","first_computed_at":"2026-05-18T00:23:57.799727Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:23:57.799727Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Xzxvh3V4hznSMEod/xcLS3eNuArfv0AVw/Scu7OhrJEWpP+FEGKn13nRrSue2P3Drch3erGkB5ZcM2aucRTiDw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:23:57.800283Z","signed_message":"canonical_sha256_bytes"},"source_id":"1802.03375","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:09de77a04b836a8a79679b82df50a8d3c256bbae201d30c7abe919ed2c5344d6","sha256:a1af0186437ce88f78fec8a901fd9212a01b6a2f7cb410954f3a698ae1398db4"],"state_sha256":"34ae9a1128796c428115d8641459113088223937c240890fd8d045946691f592"}