{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:L3BSYQDBE4A4CNL5J6WVFIDOFB","short_pith_number":"pith:L3BSYQDB","canonical_record":{"source":{"id":"2402.01117","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-02-02T03:21:00Z","cross_cats_sorted":["cs.DB","cs.HC"],"title_canon_sha256":"35c73cbf5f0f7a8332833f50b56c37def94d9fce80b6074442c4ad2b4d2825db","abstract_canon_sha256":"ad157f54f864b897d697ba39f3866692aebcdce58303cd87a394d91bb2e20658"},"schema_version":"1.0"},"canonical_sha256":"5ec32c40612701c1357d4fad52a06e2867b4804d4487719b4c83bc43c40ffadb","source":{"kind":"arxiv","id":"2402.01117","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.01117","created_at":"2026-07-05T07:40:30Z"},{"alias_kind":"arxiv_version","alias_value":"2402.01117v1","created_at":"2026-07-05T07:40:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.01117","created_at":"2026-07-05T07:40:30Z"},{"alias_kind":"pith_short_12","alias_value":"L3BSYQDBE4A4","created_at":"2026-07-05T07:40:30Z"},{"alias_kind":"pith_short_16","alias_value":"L3BSYQDBE4A4CNL5","created_at":"2026-07-05T07:40:30Z"},{"alias_kind":"pith_short_8","alias_value":"L3BSYQDB","created_at":"2026-07-05T07:40:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:L3BSYQDBE4A4CNL5J6WVFIDOFB","target":"record","payload":{"canonical_record":{"source":{"id":"2402.01117","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-02-02T03:21:00Z","cross_cats_sorted":["cs.DB","cs.HC"],"title_canon_sha256":"35c73cbf5f0f7a8332833f50b56c37def94d9fce80b6074442c4ad2b4d2825db","abstract_canon_sha256":"ad157f54f864b897d697ba39f3866692aebcdce58303cd87a394d91bb2e20658"},"schema_version":"1.0"},"canonical_sha256":"5ec32c40612701c1357d4fad52a06e2867b4804d4487719b4c83bc43c40ffadb","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:40:30.965552Z","signature_b64":"kreOxRMq54Z6A9btz7Rk0+HcbKb/2SdI735zmAhqRVe/KfuY62vVXsZkh1L5wHboINixMi1DIKnTwISr2iwiDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5ec32c40612701c1357d4fad52a06e2867b4804d4487719b4c83bc43c40ffadb","last_reissued_at":"2026-07-05T07:40:30.965083Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:40:30.965083Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2402.01117","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":"2026-07-05T07:40:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"P5YEC1STw4OlTBuxV2zkBLXoinXCds6hSkyYmAtdGCeoRvYAkj0Tp4O09V9mh8LGsn+nqUr3GSMU/SUCcEs6CA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T06:15:18.078517Z"},"content_sha256":"413618522070b39c6353eba713c20f5cd6c4cb3b0543a5e3957b53557c09917f","schema_version":"1.0","event_id":"sha256:413618522070b39c6353eba713c20f5cd6c4cb3b0543a5e3957b53557c09917f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:L3BSYQDBE4A4CNL5J6WVFIDOFB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DTS-SQL: Decomposed Text-to-SQL with Small Large Language Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.DB","cs.HC"],"primary_cat":"cs.CL","authors_text":"Davood Rafiei, Mohammadreza Pourreza","submitted_at":"2024-02-02T03:21:00Z","abstract_excerpt":"Leading models for the text-to-SQL task heavily rely on proprietary Large Language Models (LLMs), posing concerns over data privacy. Closing the performance gap between small open-source models and large proprietary models is crucial to mitigate this reliance. To this end, we introduce a novel two-stage fine-tuning approach that decomposes the task into two simpler tasks. Through comprehensive evaluation on two large cross-domain datasets and two small LLMs, we show that this approach improves execution accuracy by 3 to 7 percent, effectively aligning the performance of open-source models with"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.01117","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/2402.01117/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":"2026-07-05T07:40:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eGgZ7tzYHtgzbxSPD5C9wo1h5iv6Rd06YKHKbrvatdbbisEvIEXUiUedHZtKKAHQgFdrpsUxsWuNBUo+y2HEDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T06:15:18.079090Z"},"content_sha256":"ea28ab1ab918d91f5de213d450ab7e52f0c16a4b4224fdc4079c853bf542ba0a","schema_version":"1.0","event_id":"sha256:ea28ab1ab918d91f5de213d450ab7e52f0c16a4b4224fdc4079c853bf542ba0a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/L3BSYQDBE4A4CNL5J6WVFIDOFB/bundle.json","state_url":"https://pith.science/pith/L3BSYQDBE4A4CNL5J6WVFIDOFB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/L3BSYQDBE4A4CNL5J6WVFIDOFB/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":"2026-08-05T06:15:18Z","links":{"resolver":"https://pith.science/pith/L3BSYQDBE4A4CNL5J6WVFIDOFB","bundle":"https://pith.science/pith/L3BSYQDBE4A4CNL5J6WVFIDOFB/bundle.json","state":"https://pith.science/pith/L3BSYQDBE4A4CNL5J6WVFIDOFB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/L3BSYQDBE4A4CNL5J6WVFIDOFB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:L3BSYQDBE4A4CNL5J6WVFIDOFB","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":"ad157f54f864b897d697ba39f3866692aebcdce58303cd87a394d91bb2e20658","cross_cats_sorted":["cs.DB","cs.HC"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-02-02T03:21:00Z","title_canon_sha256":"35c73cbf5f0f7a8332833f50b56c37def94d9fce80b6074442c4ad2b4d2825db"},"schema_version":"1.0","source":{"id":"2402.01117","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.01117","created_at":"2026-07-05T07:40:30Z"},{"alias_kind":"arxiv_version","alias_value":"2402.01117v1","created_at":"2026-07-05T07:40:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.01117","created_at":"2026-07-05T07:40:30Z"},{"alias_kind":"pith_short_12","alias_value":"L3BSYQDBE4A4","created_at":"2026-07-05T07:40:30Z"},{"alias_kind":"pith_short_16","alias_value":"L3BSYQDBE4A4CNL5","created_at":"2026-07-05T07:40:30Z"},{"alias_kind":"pith_short_8","alias_value":"L3BSYQDB","created_at":"2026-07-05T07:40:30Z"}],"graph_snapshots":[{"event_id":"sha256:ea28ab1ab918d91f5de213d450ab7e52f0c16a4b4224fdc4079c853bf542ba0a","target":"graph","created_at":"2026-07-05T07:40:30Z","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/2402.01117/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Leading models for the text-to-SQL task heavily rely on proprietary Large Language Models (LLMs), posing concerns over data privacy. Closing the performance gap between small open-source models and large proprietary models is crucial to mitigate this reliance. To this end, we introduce a novel two-stage fine-tuning approach that decomposes the task into two simpler tasks. Through comprehensive evaluation on two large cross-domain datasets and two small LLMs, we show that this approach improves execution accuracy by 3 to 7 percent, effectively aligning the performance of open-source models with","authors_text":"Davood Rafiei, Mohammadreza Pourreza","cross_cats":["cs.DB","cs.HC"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-02-02T03:21:00Z","title":"DTS-SQL: Decomposed Text-to-SQL with Small Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.01117","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":"sha256:413618522070b39c6353eba713c20f5cd6c4cb3b0543a5e3957b53557c09917f","target":"record","created_at":"2026-07-05T07:40:30Z","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":"ad157f54f864b897d697ba39f3866692aebcdce58303cd87a394d91bb2e20658","cross_cats_sorted":["cs.DB","cs.HC"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-02-02T03:21:00Z","title_canon_sha256":"35c73cbf5f0f7a8332833f50b56c37def94d9fce80b6074442c4ad2b4d2825db"},"schema_version":"1.0","source":{"id":"2402.01117","kind":"arxiv","version":1}},"canonical_sha256":"5ec32c40612701c1357d4fad52a06e2867b4804d4487719b4c83bc43c40ffadb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5ec32c40612701c1357d4fad52a06e2867b4804d4487719b4c83bc43c40ffadb","first_computed_at":"2026-07-05T07:40:30.965083Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:40:30.965083Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"kreOxRMq54Z6A9btz7Rk0+HcbKb/2SdI735zmAhqRVe/KfuY62vVXsZkh1L5wHboINixMi1DIKnTwISr2iwiDw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:40:30.965552Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.01117","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:413618522070b39c6353eba713c20f5cd6c4cb3b0543a5e3957b53557c09917f","sha256:ea28ab1ab918d91f5de213d450ab7e52f0c16a4b4224fdc4079c853bf542ba0a"],"state_sha256":"e498697918828f8dc82508754adaf6c756612c179db8b82f6382f857b5c16044"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qghyp6oZRdiZsNVn+PaZqSdttoQ8SWx4iNZZCYVGqmSxQ3hRY3ZlA7QnyRHz3OYv/yp66ks8qWr7Y5Hm6OeEAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T06:15:18.084319Z","bundle_sha256":"2f310af4eec1a8c7ed93b658b56739a13ecfa99696e154b60e9411681f73369e"}}