{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:SADCSZHTIQMBRNOQ34CZ4O4SKA","short_pith_number":"pith:SADCSZHT","canonical_record":{"source":{"id":"2405.14333","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-05-23T09:03:42Z","cross_cats_sorted":[],"title_canon_sha256":"1dc362adc8492efecd46240742c9dbfb09ac4b251c1785396e03c108e4c66a13","abstract_canon_sha256":"42883e70112878e740c8f8865080cc1b0e59b346e8ca990e42f2a350714e5b8f"},"schema_version":"1.0"},"canonical_sha256":"90062964f3441818b5d0df059e3b92503d2b7a6ed89343df86ff8074620108ca","source":{"kind":"arxiv","id":"2405.14333","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.14333","created_at":"2026-07-05T08:22:13Z"},{"alias_kind":"arxiv_version","alias_value":"2405.14333v1","created_at":"2026-07-05T08:22:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.14333","created_at":"2026-07-05T08:22:13Z"},{"alias_kind":"pith_short_12","alias_value":"SADCSZHTIQMB","created_at":"2026-07-05T08:22:13Z"},{"alias_kind":"pith_short_16","alias_value":"SADCSZHTIQMBRNOQ","created_at":"2026-07-05T08:22:13Z"},{"alias_kind":"pith_short_8","alias_value":"SADCSZHT","created_at":"2026-07-05T08:22:13Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:SADCSZHTIQMBRNOQ34CZ4O4SKA","target":"record","payload":{"canonical_record":{"source":{"id":"2405.14333","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-05-23T09:03:42Z","cross_cats_sorted":[],"title_canon_sha256":"1dc362adc8492efecd46240742c9dbfb09ac4b251c1785396e03c108e4c66a13","abstract_canon_sha256":"42883e70112878e740c8f8865080cc1b0e59b346e8ca990e42f2a350714e5b8f"},"schema_version":"1.0"},"canonical_sha256":"90062964f3441818b5d0df059e3b92503d2b7a6ed89343df86ff8074620108ca","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:22:13.361923Z","signature_b64":"uymXxnn6tlyWwUzHSPQl3m/AhHFE9JITWGHReCjcbeAG1e+fPB1B4x87RbDVzMEw9BATUEf03qHn2JWWjNC1AA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"90062964f3441818b5d0df059e3b92503d2b7a6ed89343df86ff8074620108ca","last_reissued_at":"2026-07-05T08:22:13.361506Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:22:13.361506Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2405.14333","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:22:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6fm7m0JK6ocHmpL8Wp3O4RyMkiN+ibRdczYyejx8R6KDhy8a4gIyzmjcJFTvhcDDO5+Dcn/zhz0u75znyEwUCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T04:53:00.195989Z"},"content_sha256":"0cc18a9ca4f65bc0fa18c3df149d7f4350119222aec767bc2b6e6660fabd20c9","schema_version":"1.0","event_id":"sha256:0cc18a9ca4f65bc0fa18c3df149d7f4350119222aec767bc2b6e6660fabd20c9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:SADCSZHTIQMBRNOQ34CZ4O4SKA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Bo Liu, Chong Ruan, Daya Guo, Huajian Xin, Qihao Zhu, Wenda Li, Xiaodan Liang, Zhihong Shao, Zhizhou Ren","submitted_at":"2024-05-23T09:03:42Z","abstract_excerpt":"Proof assistants like Lean have revolutionized mathematical proof verification, ensuring high accuracy and reliability. Although large language models (LLMs) show promise in mathematical reasoning, their advancement in formal theorem proving is hindered by a lack of training data. To address this issue, we introduce an approach to generate extensive Lean 4 proof data derived from high-school and undergraduate-level mathematical competition problems. This approach involves translating natural language problems into formal statements, filtering out low-quality statements, and generating proofs t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.14333","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/2405.14333/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:22:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BUthXB4p9mXzgHxe4+9e96bcsnBJrm+kmlFOJGNYA3ENNzdAFhCqjqjXAjEDeod4i4fcAR0Gd/5BEGUgleE8AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T04:53:00.196432Z"},"content_sha256":"02f9210daaf54725faf74a06cd63030aca23d8367ebd27977352d5abb817be16","schema_version":"1.0","event_id":"sha256:02f9210daaf54725faf74a06cd63030aca23d8367ebd27977352d5abb817be16"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SADCSZHTIQMBRNOQ34CZ4O4SKA/bundle.json","state_url":"https://pith.science/pith/SADCSZHTIQMBRNOQ34CZ4O4SKA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SADCSZHTIQMBRNOQ34CZ4O4SKA/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-07-07T04:53:00Z","links":{"resolver":"https://pith.science/pith/SADCSZHTIQMBRNOQ34CZ4O4SKA","bundle":"https://pith.science/pith/SADCSZHTIQMBRNOQ34CZ4O4SKA/bundle.json","state":"https://pith.science/pith/SADCSZHTIQMBRNOQ34CZ4O4SKA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SADCSZHTIQMBRNOQ34CZ4O4SKA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:SADCSZHTIQMBRNOQ34CZ4O4SKA","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":"42883e70112878e740c8f8865080cc1b0e59b346e8ca990e42f2a350714e5b8f","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-05-23T09:03:42Z","title_canon_sha256":"1dc362adc8492efecd46240742c9dbfb09ac4b251c1785396e03c108e4c66a13"},"schema_version":"1.0","source":{"id":"2405.14333","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.14333","created_at":"2026-07-05T08:22:13Z"},{"alias_kind":"arxiv_version","alias_value":"2405.14333v1","created_at":"2026-07-05T08:22:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.14333","created_at":"2026-07-05T08:22:13Z"},{"alias_kind":"pith_short_12","alias_value":"SADCSZHTIQMB","created_at":"2026-07-05T08:22:13Z"},{"alias_kind":"pith_short_16","alias_value":"SADCSZHTIQMBRNOQ","created_at":"2026-07-05T08:22:13Z"},{"alias_kind":"pith_short_8","alias_value":"SADCSZHT","created_at":"2026-07-05T08:22:13Z"}],"graph_snapshots":[{"event_id":"sha256:02f9210daaf54725faf74a06cd63030aca23d8367ebd27977352d5abb817be16","target":"graph","created_at":"2026-07-05T08:22:13Z","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/2405.14333/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Proof assistants like Lean have revolutionized mathematical proof verification, ensuring high accuracy and reliability. Although large language models (LLMs) show promise in mathematical reasoning, their advancement in formal theorem proving is hindered by a lack of training data. To address this issue, we introduce an approach to generate extensive Lean 4 proof data derived from high-school and undergraduate-level mathematical competition problems. This approach involves translating natural language problems into formal statements, filtering out low-quality statements, and generating proofs t","authors_text":"Bo Liu, Chong Ruan, Daya Guo, Huajian Xin, Qihao Zhu, Wenda Li, Xiaodan Liang, Zhihong Shao, Zhizhou Ren","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-05-23T09:03:42Z","title":"DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.14333","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":"sha256:0cc18a9ca4f65bc0fa18c3df149d7f4350119222aec767bc2b6e6660fabd20c9","target":"record","created_at":"2026-07-05T08:22:13Z","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":"42883e70112878e740c8f8865080cc1b0e59b346e8ca990e42f2a350714e5b8f","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-05-23T09:03:42Z","title_canon_sha256":"1dc362adc8492efecd46240742c9dbfb09ac4b251c1785396e03c108e4c66a13"},"schema_version":"1.0","source":{"id":"2405.14333","kind":"arxiv","version":1}},"canonical_sha256":"90062964f3441818b5d0df059e3b92503d2b7a6ed89343df86ff8074620108ca","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"90062964f3441818b5d0df059e3b92503d2b7a6ed89343df86ff8074620108ca","first_computed_at":"2026-07-05T08:22:13.361506Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:22:13.361506Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"uymXxnn6tlyWwUzHSPQl3m/AhHFE9JITWGHReCjcbeAG1e+fPB1B4x87RbDVzMEw9BATUEf03qHn2JWWjNC1AA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:22:13.361923Z","signed_message":"canonical_sha256_bytes"},"source_id":"2405.14333","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0cc18a9ca4f65bc0fa18c3df149d7f4350119222aec767bc2b6e6660fabd20c9","sha256:02f9210daaf54725faf74a06cd63030aca23d8367ebd27977352d5abb817be16"],"state_sha256":"0e6bbd1a5d56124d178a676c3acf030a06761102cb1dcff689c7c5f1a503d8ff"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ne7peGVqYDXnOq8XYaHlqNEa92JX6m4/sEOOwn1ZyGF/UQM8wmYXyL6iWCxL/Mpxji+Fdo+Rz7taVu9FDs3ZCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T04:53:00.199341Z","bundle_sha256":"37a1b955f298448842e289f790d7e391e8542f26e349cbadb072daf2fe28b674"}}