{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:QGSTJI5JABMU5WZIVWMQOFEHBG","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":"a48429e6bd2845ecf5e108fe27d78d1102f27c1e6d88e1df8a5e27a5c5923883","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-10-02T14:00:09Z","title_canon_sha256":"83e64df4cda700f04ce50761af1a573f6c008aeefc69b705f8fcae511023ed63"},"schema_version":"1.0","source":{"id":"2410.01560","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.01560","created_at":"2026-07-05T09:16:22Z"},{"alias_kind":"arxiv_version","alias_value":"2410.01560v2","created_at":"2026-07-05T09:16:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.01560","created_at":"2026-07-05T09:16:22Z"},{"alias_kind":"pith_short_12","alias_value":"QGSTJI5JABMU","created_at":"2026-07-05T09:16:22Z"},{"alias_kind":"pith_short_16","alias_value":"QGSTJI5JABMU5WZI","created_at":"2026-07-05T09:16:22Z"},{"alias_kind":"pith_short_8","alias_value":"QGSTJI5J","created_at":"2026-07-05T09:16:22Z"}],"graph_snapshots":[{"event_id":"sha256:3640d1019e1b4f3199fc0810e716fa035c4f14d715701570f277e7dd6f732311","target":"graph","created_at":"2026-07-05T09:16:22Z","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/2410.01560/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Mathematical reasoning continues to be a critical challenge in large language model (LLM) development with significant interest. However, most of the cutting-edge progress in mathematical reasoning with LLMs has become \\emph{closed-source} due to lack of access to training data. This lack of data access limits researchers from understanding the impact of different choices for synthesizing and utilizing the data. With the goal of creating a high-quality finetuning (SFT) dataset for math reasoning, we conduct careful ablation experiments on data synthesis using the recently released \\texttt{Llam","authors_text":"Alexan Ayrapetyan, Branislav Kisacanin, Igor Gitman, Ivan Moshkov, Shubham Toshniwal, Wei Du","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-10-02T14:00:09Z","title":"OpenMathInstruct-2: Accelerating AI for Math with Massive Open-Source Instruction Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.01560","kind":"arxiv","version":2},"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:a5e917d19fabc09bd66071f8d985fac38c37336b1500a004c85ac370827d2d0b","target":"record","created_at":"2026-07-05T09:16:22Z","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":"a48429e6bd2845ecf5e108fe27d78d1102f27c1e6d88e1df8a5e27a5c5923883","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-10-02T14:00:09Z","title_canon_sha256":"83e64df4cda700f04ce50761af1a573f6c008aeefc69b705f8fcae511023ed63"},"schema_version":"1.0","source":{"id":"2410.01560","kind":"arxiv","version":2}},"canonical_sha256":"81a534a3a900594edb28ad9907148709ad52ae974bad64003fad9bc99ced66e8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"81a534a3a900594edb28ad9907148709ad52ae974bad64003fad9bc99ced66e8","first_computed_at":"2026-07-05T09:16:22.727807Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:16:22.727807Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"X/mGtx27PiyadtW4WOdKyl9U49dgQjEeEG8vsX5l6CfrtsyOlta945/M0gtFlSeNrgA49nJK0LkCUTQ/ONizCg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:16:22.728302Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.01560","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a5e917d19fabc09bd66071f8d985fac38c37336b1500a004c85ac370827d2d0b","sha256:3640d1019e1b4f3199fc0810e716fa035c4f14d715701570f277e7dd6f732311"],"state_sha256":"1395f08167fbf1c743957f83f703d21f4b7f6df47fa1fcb7ff11b38759ff3c97"}