{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:T34L3TWQ6S56UI64QANE5DIDXD","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":"5bc55446af7fb784eba50e3e845aac4f99dbee7a2707686c74cac877251935fb","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2022-11-14T16:52:32Z","title_canon_sha256":"93fab1c1b1e8744be825aa921d3be36653d28485f92d7bd637743c995afaae83"},"schema_version":"1.0","source":{"id":"2211.07524","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.07524","created_at":"2026-07-05T05:15:54Z"},{"alias_kind":"arxiv_version","alias_value":"2211.07524v1","created_at":"2026-07-05T05:15:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.07524","created_at":"2026-07-05T05:15:54Z"},{"alias_kind":"pith_short_12","alias_value":"T34L3TWQ6S56","created_at":"2026-07-05T05:15:54Z"},{"alias_kind":"pith_short_16","alias_value":"T34L3TWQ6S56UI64","created_at":"2026-07-05T05:15:54Z"},{"alias_kind":"pith_short_8","alias_value":"T34L3TWQ","created_at":"2026-07-05T05:15:54Z"}],"graph_snapshots":[{"event_id":"sha256:97fb45c140a3dd8b9cd738dca7d29b297d7f41011d9cde3b54fe80f0c63999a5","target":"graph","created_at":"2026-07-05T05:15:54Z","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/2211.07524/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Mathematics formalisation is the task of writing mathematics (i.e., definitions, theorem statements, proofs) in natural language, as found in books and papers, into a formal language that can then be checked for correctness by a program. It is a thriving activity today, however formalisation remains cumbersome. In this paper, we explore the abilities of a large language model (Codex) to help with formalisation in the Lean theorem prover. We find that with careful input-dependent prompt selection and postprocessing, Codex is able to formalise short mathematical statements at undergrad level wit","authors_text":"Anand Tadipatri, Ashvni Narayanan, Ayush Agrawal, Navin Goyal, Siddhartha Gadgil","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2022-11-14T16:52:32Z","title":"Towards a Mathematics Formalisation Assistant using Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.07524","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:d402ca470b97694eeebf7e9f9a139e82701ec54fa9e410f61cb1a24603a14a25","target":"record","created_at":"2026-07-05T05:15:54Z","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":"5bc55446af7fb784eba50e3e845aac4f99dbee7a2707686c74cac877251935fb","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2022-11-14T16:52:32Z","title_canon_sha256":"93fab1c1b1e8744be825aa921d3be36653d28485f92d7bd637743c995afaae83"},"schema_version":"1.0","source":{"id":"2211.07524","kind":"arxiv","version":1}},"canonical_sha256":"9ef8bdced0f4bbea23dc801a4e8d03b8f970fbf74f8b40041a12cc8edf751c23","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9ef8bdced0f4bbea23dc801a4e8d03b8f970fbf74f8b40041a12cc8edf751c23","first_computed_at":"2026-07-05T05:15:54.590986Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:15:54.590986Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Q/5lbu/jy0iaNPuvxB7RhVXORzK2rYo8Lhd4utctBztq1QydlCjsf/P/E0g3zA4vfLzAhPoBbqT+QHGYRLCAAA==","signature_status":"signed_v1","signed_at":"2026-07-05T05:15:54.591391Z","signed_message":"canonical_sha256_bytes"},"source_id":"2211.07524","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d402ca470b97694eeebf7e9f9a139e82701ec54fa9e410f61cb1a24603a14a25","sha256:97fb45c140a3dd8b9cd738dca7d29b297d7f41011d9cde3b54fe80f0c63999a5"],"state_sha256":"835bc3c3ece0ff78f3df58f0064aa7298a3af37f509d34454c021b18f6c83377"}