{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:BRMIIGMF73RWMV3WPQHVVMTAHA","short_pith_number":"pith:BRMIIGMF","canonical_record":{"source":{"id":"2503.02240","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-03-04T03:30:56Z","cross_cats_sorted":["cs.DB"],"title_canon_sha256":"0b6e53ba549854a2461003ab9f0d49b1b97feb4f62863e12d0791c1cd4a84e0b","abstract_canon_sha256":"a3bf42728b189d91f28e6b581cf827b7c9dd92408325db36fdb3cb82ccc23b5d"},"schema_version":"1.0"},"canonical_sha256":"0c58841985fee36657767c0f5ab260381892fb22cf4d6a40e8e320c384bc0004","source":{"kind":"arxiv","id":"2503.02240","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.02240","created_at":"2026-07-05T11:36:29Z"},{"alias_kind":"arxiv_version","alias_value":"2503.02240v2","created_at":"2026-07-05T11:36:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.02240","created_at":"2026-07-05T11:36:29Z"},{"alias_kind":"pith_short_12","alias_value":"BRMIIGMF73RW","created_at":"2026-07-05T11:36:29Z"},{"alias_kind":"pith_short_16","alias_value":"BRMIIGMF73RWMV3W","created_at":"2026-07-05T11:36:29Z"},{"alias_kind":"pith_short_8","alias_value":"BRMIIGMF","created_at":"2026-07-05T11:36:29Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:BRMIIGMF73RWMV3WPQHVVMTAHA","target":"record","payload":{"canonical_record":{"source":{"id":"2503.02240","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-03-04T03:30:56Z","cross_cats_sorted":["cs.DB"],"title_canon_sha256":"0b6e53ba549854a2461003ab9f0d49b1b97feb4f62863e12d0791c1cd4a84e0b","abstract_canon_sha256":"a3bf42728b189d91f28e6b581cf827b7c9dd92408325db36fdb3cb82ccc23b5d"},"schema_version":"1.0"},"canonical_sha256":"0c58841985fee36657767c0f5ab260381892fb22cf4d6a40e8e320c384bc0004","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:36:29.026986Z","signature_b64":"TR9RMf1eM3TvbU4Z8nsbNkLarpHHV8h/PRMt7/KemFdDa5x5qQBUh17fgwyjDANvHZhrIn8Hjc41SJ5mgDiyBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0c58841985fee36657767c0f5ab260381892fb22cf4d6a40e8e320c384bc0004","last_reissued_at":"2026-07-05T11:36:29.026487Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:36:29.026487Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2503.02240","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:36:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"badtnatAvQTBI+v7iQPX/L17nS+JESoPooDRmsUIcUQPgUsBvQAgrQYBbPETNxNaBI+81ZJz8tBbdQkPAiiCCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T12:45:12.936817Z"},"content_sha256":"1abad903ba73c4df6f4fe167cb31edae9a578bff137b52f2e76430a24054b380","schema_version":"1.0","event_id":"sha256:1abad903ba73c4df6f4fe167cb31edae9a578bff137b52f2e76430a24054b380"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:BRMIIGMF73RWMV3WPQHVVMTAHA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"OmniSQL: Synthesizing High-quality Text-to-SQL Data at Scale","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DB"],"primary_cat":"cs.CL","authors_text":"Cuiping Li, Fuxin Jiang, Haoyang Li, Hong Chen, Jianjun Chen, Jing Zhang, Rui Shi, Shang Wu, Shuai Wang, Tieying Zhang, Xiaokang Zhang, Xinmei Huang","submitted_at":"2025-03-04T03:30:56Z","abstract_excerpt":"Text-to-SQL, the task of translating natural language questions into SQL queries, plays a crucial role in enabling non-experts to interact with databases. While recent advancements in large language models (LLMs) have significantly enhanced text-to-SQL performance, existing approaches face notable limitations in real-world text-to-SQL applications. Prompting-based methods often depend on closed-source LLMs, which are expensive, raise privacy concerns, and lack customization. Fine-tuning-based methods, on the other hand, suffer from poor generalizability due to the limited coverage of publicly "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.02240","kind":"arxiv","version":2},"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/2503.02240/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":"2026-07-05T11:36:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hu21hKJJgm5yjVW9BDHTaZW7aTKqTGuWCu/OOsL4N4qlxY1X4gs+DrPGFL7G6JypefuNASnuY9JlKu9tJGR9Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T12:45:12.937320Z"},"content_sha256":"feed5e64a594e8046adfd2fbdbbe61df929b832623826e827ef7f6bc1d82a00a","schema_version":"1.0","event_id":"sha256:feed5e64a594e8046adfd2fbdbbe61df929b832623826e827ef7f6bc1d82a00a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BRMIIGMF73RWMV3WPQHVVMTAHA/bundle.json","state_url":"https://pith.science/pith/BRMIIGMF73RWMV3WPQHVVMTAHA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BRMIIGMF73RWMV3WPQHVVMTAHA/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":"2026-08-10T12:45:12Z","links":{"resolver":"https://pith.science/pith/BRMIIGMF73RWMV3WPQHVVMTAHA","bundle":"https://pith.science/pith/BRMIIGMF73RWMV3WPQHVVMTAHA/bundle.json","state":"https://pith.science/pith/BRMIIGMF73RWMV3WPQHVVMTAHA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BRMIIGMF73RWMV3WPQHVVMTAHA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:BRMIIGMF73RWMV3WPQHVVMTAHA","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":"a3bf42728b189d91f28e6b581cf827b7c9dd92408325db36fdb3cb82ccc23b5d","cross_cats_sorted":["cs.DB"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-03-04T03:30:56Z","title_canon_sha256":"0b6e53ba549854a2461003ab9f0d49b1b97feb4f62863e12d0791c1cd4a84e0b"},"schema_version":"1.0","source":{"id":"2503.02240","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.02240","created_at":"2026-07-05T11:36:29Z"},{"alias_kind":"arxiv_version","alias_value":"2503.02240v2","created_at":"2026-07-05T11:36:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.02240","created_at":"2026-07-05T11:36:29Z"},{"alias_kind":"pith_short_12","alias_value":"BRMIIGMF73RW","created_at":"2026-07-05T11:36:29Z"},{"alias_kind":"pith_short_16","alias_value":"BRMIIGMF73RWMV3W","created_at":"2026-07-05T11:36:29Z"},{"alias_kind":"pith_short_8","alias_value":"BRMIIGMF","created_at":"2026-07-05T11:36:29Z"}],"graph_snapshots":[{"event_id":"sha256:feed5e64a594e8046adfd2fbdbbe61df929b832623826e827ef7f6bc1d82a00a","target":"graph","created_at":"2026-07-05T11:36:29Z","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/2503.02240/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Text-to-SQL, the task of translating natural language questions into SQL queries, plays a crucial role in enabling non-experts to interact with databases. While recent advancements in large language models (LLMs) have significantly enhanced text-to-SQL performance, existing approaches face notable limitations in real-world text-to-SQL applications. Prompting-based methods often depend on closed-source LLMs, which are expensive, raise privacy concerns, and lack customization. Fine-tuning-based methods, on the other hand, suffer from poor generalizability due to the limited coverage of publicly ","authors_text":"Cuiping Li, Fuxin Jiang, Haoyang Li, Hong Chen, Jianjun Chen, Jing Zhang, Rui Shi, Shang Wu, Shuai Wang, Tieying Zhang, Xiaokang Zhang, Xinmei Huang","cross_cats":["cs.DB"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-03-04T03:30:56Z","title":"OmniSQL: Synthesizing High-quality Text-to-SQL Data at Scale"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.02240","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":"sha256:1abad903ba73c4df6f4fe167cb31edae9a578bff137b52f2e76430a24054b380","target":"record","created_at":"2026-07-05T11:36:29Z","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":"a3bf42728b189d91f28e6b581cf827b7c9dd92408325db36fdb3cb82ccc23b5d","cross_cats_sorted":["cs.DB"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-03-04T03:30:56Z","title_canon_sha256":"0b6e53ba549854a2461003ab9f0d49b1b97feb4f62863e12d0791c1cd4a84e0b"},"schema_version":"1.0","source":{"id":"2503.02240","kind":"arxiv","version":2}},"canonical_sha256":"0c58841985fee36657767c0f5ab260381892fb22cf4d6a40e8e320c384bc0004","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0c58841985fee36657767c0f5ab260381892fb22cf4d6a40e8e320c384bc0004","first_computed_at":"2026-07-05T11:36:29.026487Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:36:29.026487Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"TR9RMf1eM3TvbU4Z8nsbNkLarpHHV8h/PRMt7/KemFdDa5x5qQBUh17fgwyjDANvHZhrIn8Hjc41SJ5mgDiyBw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:36:29.026986Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.02240","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1abad903ba73c4df6f4fe167cb31edae9a578bff137b52f2e76430a24054b380","sha256:feed5e64a594e8046adfd2fbdbbe61df929b832623826e827ef7f6bc1d82a00a"],"state_sha256":"48e9240d63e5d54235423b2a2423bd1fc44c1b33d3bdf6d082b65bcbfb9fde4c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cI9ZCIxhTalC2XKy5Xnb1vHQWn/+JAmS/DAbWoftZHRCgSOPQoKiAQXZgJkP4EqlC0llMHqzHN3ugkogKRy1CA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T12:45:12.941715Z","bundle_sha256":"6a8fc4bdf1f9ab14dfc7dea7600546d33185a2f808e280a2ae72bb898cca32ba"}}