{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:RRONDHDQSINOCMQOYWD5J2LYYH","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":"a72267dcbb0de6f69bede7da04be09158f4d2e8aafb4ac9a5a3005c964a80b75","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LO","submitted_at":"2020-06-19T17:48:09Z","title_canon_sha256":"d43b7c6df01a445e137efaa801fd251b97fdeb3367e2410f52f668268997a1fd"},"schema_version":"1.0","source":{"id":"2006.11259","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2006.11259","created_at":"2026-07-05T01:11:36Z"},{"alias_kind":"arxiv_version","alias_value":"2006.11259v1","created_at":"2026-07-05T01:11:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2006.11259","created_at":"2026-07-05T01:11:36Z"},{"alias_kind":"pith_short_12","alias_value":"RRONDHDQSINO","created_at":"2026-07-05T01:11:36Z"},{"alias_kind":"pith_short_16","alias_value":"RRONDHDQSINOCMQO","created_at":"2026-07-05T01:11:36Z"},{"alias_kind":"pith_short_8","alias_value":"RRONDHDQ","created_at":"2026-07-05T01:11:36Z"}],"graph_snapshots":[{"event_id":"sha256:0381b8e0295f7ec822865ec13ba71a24617e4bdb0bc3cf4ac1c198925296362d","target":"graph","created_at":"2026-07-05T01:11:36Z","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/2006.11259/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"A major challenge in applying machine learning to automated theorem proving is the scarcity of training data, which is a key ingredient in training successful deep learning models. To tackle this problem, we propose an approach that relies on training with synthetic theorems, generated from a set of axioms. We show that such theorems can be used to train an automated prover and that the learned prover transfers successfully to human-generated theorems. We demonstrate that a prover trained exclusively on synthetic theorems can solve a substantial fraction of problems in TPTP, a benchmark datase","authors_text":"Ankit Anand, Doina Precup, Eser Ayg\\\"un, Laurent Orseau, Shibl Mourad, Vlad Firoiu, Xavier Glorot, Zafarali Ahmed","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LO","submitted_at":"2020-06-19T17:48:09Z","title":"Learning to Prove from Synthetic Theorems"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2006.11259","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":"sha256:50fdf8a5ee61281652ab1df37a77c4a35188792994df5cfcb01dc8af40a9c35c","target":"record","created_at":"2026-07-05T01:11:36Z","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":"a72267dcbb0de6f69bede7da04be09158f4d2e8aafb4ac9a5a3005c964a80b75","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LO","submitted_at":"2020-06-19T17:48:09Z","title_canon_sha256":"d43b7c6df01a445e137efaa801fd251b97fdeb3367e2410f52f668268997a1fd"},"schema_version":"1.0","source":{"id":"2006.11259","kind":"arxiv","version":1}},"canonical_sha256":"8c5cd19c70921ae1320ec587d4e978c1c471d77d2ca840efb7884c7f3845c4f2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8c5cd19c70921ae1320ec587d4e978c1c471d77d2ca840efb7884c7f3845c4f2","first_computed_at":"2026-07-05T01:11:36.841217Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:11:36.841217Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"6cIc/+C/RUXJPjYpSIhg/ZpJyOHusc5c8dq0X5Z0bRG5eIzWUQokeifIZoTJ9dKT2HDnBtJECeDFqbIspAfGBA==","signature_status":"signed_v1","signed_at":"2026-07-05T01:11:36.841635Z","signed_message":"canonical_sha256_bytes"},"source_id":"2006.11259","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:50fdf8a5ee61281652ab1df37a77c4a35188792994df5cfcb01dc8af40a9c35c","sha256:0381b8e0295f7ec822865ec13ba71a24617e4bdb0bc3cf4ac1c198925296362d"],"state_sha256":"6cb8830ac510e7ac8b2f652d8bf2a755d8b4d6c38e8238ad11d731405eaaca67"}