{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:ILSNXQ5JPGDKE2IKTSZ2TUQKVR","short_pith_number":"pith:ILSNXQ5J","schema_version":"1.0","canonical_sha256":"42e4dbc3a97986a2690a9cb3a9d20aac77851bed406d9d659514b907180a55fb","source":{"kind":"arxiv","id":"2608.10894","version":1},"attestation_state":"computed","paper":{"title":"FormaTheoria: Constructing Large-Scale Lean Theories from Mathematical Literature $-$ Toward the Formalization of the Classification of Finite Simple Groups","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.GR"],"primary_cat":"cs.LO","authors_text":"Ao Zhang, Damiano Testa, Peng Li, Shing-Tung Yau, Tianjiao Nie, Yuan Zhou, Yusen Tang","submitted_at":"2026-08-11T13:13:11Z","abstract_excerpt":"Large-scale formalization of advanced mathematics requires more than translating individual statements: it must reconstruct a coherent theory distributed across heterogeneous sources. This process raises four challenges: discovering implicit dependencies, correcting source defects, preserving semantic fidelity, and reconciling cross-source misalignments. We present FormaTheoria, an end-to-end, AI-assisted workflow that coordinates source acquisition, formalization, proof construction, recursive dependency discovery, independent review, and reconciliation, while preserving provenance and protec"},"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":"2608.10894","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LO","submitted_at":"2026-08-11T13:13:11Z","cross_cats_sorted":["math.GR"],"title_canon_sha256":"871f47c65b9b0eda3506d3d8888171ea5e2da5657c2f385554a1dd0a45bae3df","abstract_canon_sha256":"29939b1199d29a2eb5c7c98026b9bab11d5635e871d781ddc2206fd29289c9d2"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-12T01:23:45.378298Z","signature_b64":"NNxbXwLiaaEJ/kx/yoD8noXmTtfOGuf8owcHpEePoQd/z6StObGu/shg5viU2/CQAnHq4NSQ1sh6sm4zV0nLCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"42e4dbc3a97986a2690a9cb3a9d20aac77851bed406d9d659514b907180a55fb","last_reissued_at":"2026-08-12T01:23:45.375820Z","signature_status":"signed_v1","first_computed_at":"2026-08-12T01:23:45.375820Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"FormaTheoria: Constructing Large-Scale Lean Theories from Mathematical Literature $-$ Toward the Formalization of the Classification of Finite Simple Groups","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.GR"],"primary_cat":"cs.LO","authors_text":"Ao Zhang, Damiano Testa, Peng Li, Shing-Tung Yau, Tianjiao Nie, Yuan Zhou, Yusen Tang","submitted_at":"2026-08-11T13:13:11Z","abstract_excerpt":"Large-scale formalization of advanced mathematics requires more than translating individual statements: it must reconstruct a coherent theory distributed across heterogeneous sources. This process raises four challenges: discovering implicit dependencies, correcting source defects, preserving semantic fidelity, and reconciling cross-source misalignments. We present FormaTheoria, an end-to-end, AI-assisted workflow that coordinates source acquisition, formalization, proof construction, recursive dependency discovery, independent review, and reconciliation, while preserving provenance and protec"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.10894","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/2608.10894/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":"2608.10894","created_at":"2026-08-12T01:23:45.380154+00:00"},{"alias_kind":"arxiv_version","alias_value":"2608.10894v1","created_at":"2026-08-12T01:23:45.380154+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.10894","created_at":"2026-08-12T01:23:45.380154+00:00"},{"alias_kind":"pith_short_12","alias_value":"ILSNXQ5JPGDK","created_at":"2026-08-12T01:23:45.380154+00:00"},{"alias_kind":"pith_short_16","alias_value":"ILSNXQ5JPGDKE2IK","created_at":"2026-08-12T01:23:45.380154+00:00"},{"alias_kind":"pith_short_8","alias_value":"ILSNXQ5J","created_at":"2026-08-12T01:23:45.380154+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/ILSNXQ5JPGDKE2IKTSZ2TUQKVR","json":"https://pith.science/pith/ILSNXQ5JPGDKE2IKTSZ2TUQKVR.json","graph_json":"https://pith.science/api/pith-number/ILSNXQ5JPGDKE2IKTSZ2TUQKVR/graph.json","events_json":"https://pith.science/api/pith-number/ILSNXQ5JPGDKE2IKTSZ2TUQKVR/events.json","paper":"https://pith.science/paper/ILSNXQ5J"},"agent_actions":{"view_html":"https://pith.science/pith/ILSNXQ5JPGDKE2IKTSZ2TUQKVR","download_json":"https://pith.science/pith/ILSNXQ5JPGDKE2IKTSZ2TUQKVR.json","view_paper":"https://pith.science/paper/ILSNXQ5J","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2608.10894&json=true","fetch_graph":"https://pith.science/api/pith-number/ILSNXQ5JPGDKE2IKTSZ2TUQKVR/graph.json","fetch_events":"https://pith.science/api/pith-number/ILSNXQ5JPGDKE2IKTSZ2TUQKVR/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ILSNXQ5JPGDKE2IKTSZ2TUQKVR/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ILSNXQ5JPGDKE2IKTSZ2TUQKVR/action/storage_attestation","attest_author":"https://pith.science/pith/ILSNXQ5JPGDKE2IKTSZ2TUQKVR/action/author_attestation","sign_citation":"https://pith.science/pith/ILSNXQ5JPGDKE2IKTSZ2TUQKVR/action/citation_signature","submit_replication":"https://pith.science/pith/ILSNXQ5JPGDKE2IKTSZ2TUQKVR/action/replication_record"}},"created_at":"2026-08-12T01:23:45.380154+00:00","updated_at":"2026-08-12T01:23:45.380154+00:00"}