{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:XR2WMGCW7E2SMTQWCXZEDKVXTW","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":"1d6a3ad984c44dc4eaec449e94edfd211ed2f6bdde80f96ce91209d2f504bed5","cross_cats_sorted":["cs.AI","cs.CL","math.HO"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-11-12T07:52:32Z","title_canon_sha256":"4c540d676a994b0f2d37b08f271b02e5c81cf3c4736bbb9b4892cdc42ee458d1"},"schema_version":"1.0","source":{"id":"2311.07618","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.07618","created_at":"2026-07-05T07:12:21Z"},{"alias_kind":"arxiv_version","alias_value":"2311.07618v1","created_at":"2026-07-05T07:12:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.07618","created_at":"2026-07-05T07:12:21Z"},{"alias_kind":"pith_short_12","alias_value":"XR2WMGCW7E2S","created_at":"2026-07-05T07:12:21Z"},{"alias_kind":"pith_short_16","alias_value":"XR2WMGCW7E2SMTQW","created_at":"2026-07-05T07:12:21Z"},{"alias_kind":"pith_short_8","alias_value":"XR2WMGCW","created_at":"2026-07-05T07:12:21Z"}],"graph_snapshots":[{"event_id":"sha256:33f1ccd2b4b6254e438c46b47baff37b04dad65beefe28634f167c2dcbc8e17f","target":"graph","created_at":"2026-07-05T07:12:21Z","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/2311.07618/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"It has been suggested that large language models such as GPT-4 have acquired some form of understanding beyond the correlations among the words in text including some understanding of mathematics as well. Here, we perform a critical inquiry into this claim by evaluating the mathematical understanding of the GPT-4 model. Considering that GPT-4's training set is a secret, it is not straightforward to evaluate whether the model's correct answers are based on a mathematical understanding or based on replication of proofs that the model has seen before. We specifically craft mathematical questions ","authors_text":"Roozbeh Yousefzadeh, Xuenan Cao","cross_cats":["cs.AI","cs.CL","math.HO"],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-11-12T07:52:32Z","title":"Large Language Models' Understanding of Math: Source Criticism and Extrapolation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.07618","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":"sha256:055140af7b59a98e1981598f981496644b67a1d2fe7c96ac9fa580f7dbece564","target":"record","created_at":"2026-07-05T07:12:21Z","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":"1d6a3ad984c44dc4eaec449e94edfd211ed2f6bdde80f96ce91209d2f504bed5","cross_cats_sorted":["cs.AI","cs.CL","math.HO"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-11-12T07:52:32Z","title_canon_sha256":"4c540d676a994b0f2d37b08f271b02e5c81cf3c4736bbb9b4892cdc42ee458d1"},"schema_version":"1.0","source":{"id":"2311.07618","kind":"arxiv","version":1}},"canonical_sha256":"bc75661856f935264e1615f241aab79db905734d1f0d8e55bac8d320312df97b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bc75661856f935264e1615f241aab79db905734d1f0d8e55bac8d320312df97b","first_computed_at":"2026-07-05T07:12:21.171752Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:12:21.171752Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"p6PEhXBwe1ozh7ErtbEnE1d0ZTTTkW08vf0/F5PZ2t91d7QkKKZ9FkkKAtLYGosh/VoZVOPU94aSG99SXSUyCw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:12:21.172084Z","signed_message":"canonical_sha256_bytes"},"source_id":"2311.07618","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:055140af7b59a98e1981598f981496644b67a1d2fe7c96ac9fa580f7dbece564","sha256:33f1ccd2b4b6254e438c46b47baff37b04dad65beefe28634f167c2dcbc8e17f"],"state_sha256":"c1fc4f568622650ab729d39258231a20255efbfa9333f09b0614cf2861fc4db1"}