{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:JLSQMAU643MPFRBIITWXT7MFKM","short_pith_number":"pith:JLSQMAU6","canonical_record":{"source":{"id":"2404.00344","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-03-30T12:48:31Z","cross_cats_sorted":["cs.AI","cs.IR"],"title_canon_sha256":"0a17993728dd6886f021eb3b4396a160a1e0830e1c32afe8841312b3776b3e3c","abstract_canon_sha256":"21d9047f5bd277c4f0cadf8e9887d6117663534d1e22465422b75b262f5b7e5b"},"schema_version":"1.0"},"canonical_sha256":"4ae506029ee6d8f2c42844ed79fd85530635cf0586a5932d1aea53943b560b77","source":{"kind":"arxiv","id":"2404.00344","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.00344","created_at":"2026-07-05T08:02:31Z"},{"alias_kind":"arxiv_version","alias_value":"2404.00344v1","created_at":"2026-07-05T08:02:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.00344","created_at":"2026-07-05T08:02:31Z"},{"alias_kind":"pith_short_12","alias_value":"JLSQMAU643MP","created_at":"2026-07-05T08:02:31Z"},{"alias_kind":"pith_short_16","alias_value":"JLSQMAU643MPFRBI","created_at":"2026-07-05T08:02:31Z"},{"alias_kind":"pith_short_8","alias_value":"JLSQMAU6","created_at":"2026-07-05T08:02:31Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:JLSQMAU643MPFRBIITWXT7MFKM","target":"record","payload":{"canonical_record":{"source":{"id":"2404.00344","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-03-30T12:48:31Z","cross_cats_sorted":["cs.AI","cs.IR"],"title_canon_sha256":"0a17993728dd6886f021eb3b4396a160a1e0830e1c32afe8841312b3776b3e3c","abstract_canon_sha256":"21d9047f5bd277c4f0cadf8e9887d6117663534d1e22465422b75b262f5b7e5b"},"schema_version":"1.0"},"canonical_sha256":"4ae506029ee6d8f2c42844ed79fd85530635cf0586a5932d1aea53943b560b77","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:02:31.813077Z","signature_b64":"kd2L9+ZMGnjUf2w6lDh2OL0Bzo4GUguAwcIUH+o3UrfrGRwJ8TvpbCFhyfDXAjkT5kgsX0mkopwc/X//ZjpCDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4ae506029ee6d8f2c42844ed79fd85530635cf0586a5932d1aea53943b560b77","last_reissued_at":"2026-07-05T08:02:31.812542Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:02:31.812542Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2404.00344","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":"2026-07-05T08:02:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6TVIOOfKPYsHrca/z3QfBpu8J18MTPIR5AEPfh/x3jUtevAvv8nDMax6Zg1gEk93JbgWernyFKX7bQwj/SQzAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T14:29:31.734227Z"},"content_sha256":"33428016cb877149a6c1dcc0830a938e391a929b5692f0ee50aba7da9eebad53","schema_version":"1.0","event_id":"sha256:33428016cb877149a6c1dcc0830a938e391a929b5692f0ee50aba7da9eebad53"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:JLSQMAU643MPFRBIITWXT7MFKM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Can LLMs Master Math? Investigating Large Language Models on Math Stack Exchange","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI","cs.IR"],"primary_cat":"cs.CL","authors_text":"Akiko Aizawa, Andre Greiner-Petter, Ankit Satpute, Bela Gipp, Moritz Schubotz, Noah Giessing, Olaf Teschke","submitted_at":"2024-03-30T12:48:31Z","abstract_excerpt":"Large Language Models (LLMs) have demonstrated exceptional capabilities in various natural language tasks, often achieving performances that surpass those of humans. Despite these advancements, the domain of mathematics presents a distinctive challenge, primarily due to its specialized structure and the precision it demands. In this study, we adopted a two-step approach for investigating the proficiency of LLMs in answering mathematical questions. First, we employ the most effective LLMs, as identified by their performance on math question-answer benchmarks, to generate answers to 78 questions"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.00344","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/2404.00344/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":"2026-07-05T08:02:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uFnkCzwLeyjDp0RA3gtLlI1+YDFRxYa1uHEjdKGqH2gqz4nzcAQa8nwNNXNgmcBu1gclrv7od6RrFSCHPHJaAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T14:29:31.734609Z"},"content_sha256":"580fd1e34e31a1d0a7c027a078f659e24e86f84b84922cc41e94c76c488eed1d","schema_version":"1.0","event_id":"sha256:580fd1e34e31a1d0a7c027a078f659e24e86f84b84922cc41e94c76c488eed1d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/JLSQMAU643MPFRBIITWXT7MFKM/bundle.json","state_url":"https://pith.science/pith/JLSQMAU643MPFRBIITWXT7MFKM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/JLSQMAU643MPFRBIITWXT7MFKM/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":"2026-07-06T14:29:31Z","links":{"resolver":"https://pith.science/pith/JLSQMAU643MPFRBIITWXT7MFKM","bundle":"https://pith.science/pith/JLSQMAU643MPFRBIITWXT7MFKM/bundle.json","state":"https://pith.science/pith/JLSQMAU643MPFRBIITWXT7MFKM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/JLSQMAU643MPFRBIITWXT7MFKM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:JLSQMAU643MPFRBIITWXT7MFKM","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":"21d9047f5bd277c4f0cadf8e9887d6117663534d1e22465422b75b262f5b7e5b","cross_cats_sorted":["cs.AI","cs.IR"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-03-30T12:48:31Z","title_canon_sha256":"0a17993728dd6886f021eb3b4396a160a1e0830e1c32afe8841312b3776b3e3c"},"schema_version":"1.0","source":{"id":"2404.00344","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2404.00344","created_at":"2026-07-05T08:02:31Z"},{"alias_kind":"arxiv_version","alias_value":"2404.00344v1","created_at":"2026-07-05T08:02:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2404.00344","created_at":"2026-07-05T08:02:31Z"},{"alias_kind":"pith_short_12","alias_value":"JLSQMAU643MP","created_at":"2026-07-05T08:02:31Z"},{"alias_kind":"pith_short_16","alias_value":"JLSQMAU643MPFRBI","created_at":"2026-07-05T08:02:31Z"},{"alias_kind":"pith_short_8","alias_value":"JLSQMAU6","created_at":"2026-07-05T08:02:31Z"}],"graph_snapshots":[{"event_id":"sha256:580fd1e34e31a1d0a7c027a078f659e24e86f84b84922cc41e94c76c488eed1d","target":"graph","created_at":"2026-07-05T08:02:31Z","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/2404.00344/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) have demonstrated exceptional capabilities in various natural language tasks, often achieving performances that surpass those of humans. Despite these advancements, the domain of mathematics presents a distinctive challenge, primarily due to its specialized structure and the precision it demands. In this study, we adopted a two-step approach for investigating the proficiency of LLMs in answering mathematical questions. First, we employ the most effective LLMs, as identified by their performance on math question-answer benchmarks, to generate answers to 78 questions","authors_text":"Akiko Aizawa, Andre Greiner-Petter, Ankit Satpute, Bela Gipp, Moritz Schubotz, Noah Giessing, Olaf Teschke","cross_cats":["cs.AI","cs.IR"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-03-30T12:48:31Z","title":"Can LLMs Master Math? Investigating Large Language Models on Math Stack Exchange"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2404.00344","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":"sha256:33428016cb877149a6c1dcc0830a938e391a929b5692f0ee50aba7da9eebad53","target":"record","created_at":"2026-07-05T08:02:31Z","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":"21d9047f5bd277c4f0cadf8e9887d6117663534d1e22465422b75b262f5b7e5b","cross_cats_sorted":["cs.AI","cs.IR"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-03-30T12:48:31Z","title_canon_sha256":"0a17993728dd6886f021eb3b4396a160a1e0830e1c32afe8841312b3776b3e3c"},"schema_version":"1.0","source":{"id":"2404.00344","kind":"arxiv","version":1}},"canonical_sha256":"4ae506029ee6d8f2c42844ed79fd85530635cf0586a5932d1aea53943b560b77","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4ae506029ee6d8f2c42844ed79fd85530635cf0586a5932d1aea53943b560b77","first_computed_at":"2026-07-05T08:02:31.812542Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:02:31.812542Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"kd2L9+ZMGnjUf2w6lDh2OL0Bzo4GUguAwcIUH+o3UrfrGRwJ8TvpbCFhyfDXAjkT5kgsX0mkopwc/X//ZjpCDw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:02:31.813077Z","signed_message":"canonical_sha256_bytes"},"source_id":"2404.00344","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:33428016cb877149a6c1dcc0830a938e391a929b5692f0ee50aba7da9eebad53","sha256:580fd1e34e31a1d0a7c027a078f659e24e86f84b84922cc41e94c76c488eed1d"],"state_sha256":"b1eede7fb081a1171582b09bb9b099fb699db630091f24fd32ae178d5241d493"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Tr75zzrLzEKQmnAUoL9HkKt5/DnRxZltLv/nDsCY0YHqyNBarTUID/YBJxdaXapVzzfIjwcD9n0tZxFfutJhAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T14:29:31.736524Z","bundle_sha256":"2ea5582bcbbc349d39517533fa4e4d8c53a8aae299fb71dca02705ec5486d7f8"}}