{"as_of":"2026-08-08T06:17:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:73f576023b451d35200269a956eb886b8153b98aacebab54f505386e3647c1d2","coverage":[{"denominator":32,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":32,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T13:19:34.441277Z","state":"measured"},{"denominator":32,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":32,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2505.22096/citation-record","integrity":"/paper/2505.22096/integrity","json":"/paper/2505.22096/citation-record.json","paper":"/paper/2505.22096"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2305.11853","last_updated":"2023-11-27T00:42:07Z","snapshot_observed_at":"2026-07-06T15:29:50.743434Z","submitted_at":"2023-05-19T17:43:58Z","title":"How to Prompt LLMs for Text-to-SQL: A Study in Zero-shot, Single-domain, and Cross-domain Settings","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.11853","snapshot_observed_at":"2026-08-07T13:19:32.550189Z","title":"arXiv preprint arXiv:2305.11853","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.22096","last_updated":"2025-05-28T08:17:58Z","snapshot_observed_at":"2026-08-07T13:12:54.131841Z","submitted_at":"2025-05-28T08:17:58Z","title":"Knowledge Base Construction for Knowledge-Augmented Text-to-SQL","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T13:19:32.550189Z"},"links":{"cited_paper":"/paper/2305.11853","citing_paper":"/paper/2505.22096"},"observation_digest":"sha256:7d1bfec69abfaa5f741f62fba19352065ee469abcca2af76c01a3361116ed0f3","observation_id":"8b8b45b2-e0f5-491a-acf0-6230e199ba87","resolution":{"observed_at":"2026-08-07T13:19:32.550189Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.07306","last_updated":"2023-07-14T12:30:41Z","snapshot_observed_at":"2026-07-06T15:54:01.430352Z","submitted_at":"2023-07-14T12:30:41Z","title":"C3: Zero-shot Text-to-SQL with ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.07306","snapshot_observed_at":"2026-08-07T13:19:32.760289Z","title":"arXiv preprint arXiv:2307.07306","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.22096","last_updated":"2025-05-28T08:17:58Z","snapshot_observed_at":"2026-08-07T13:12:54.131841Z","submitted_at":"2025-05-28T08:17:58Z","title":"Knowledge Base Construction for Knowledge-Augmented Text-to-SQL","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T13:19:32.760289Z"},"links":{"cited_paper":"/paper/2307.07306","citing_paper":"/paper/2505.22096"},"observation_digest":"sha256:960aeb87c40619d656196da92566c3034fca7d72c0bdeb080e335526d029d907","observation_id":"cbf1b5ac-4bec-4c3b-9abd-96495b79f95d","resolution":{"observed_at":"2026-08-07T13:19:32.760289Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:19:36.255088Z","title":"In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022, Abu Dhabi, United Arab Emirates, December 7-11, 2022, pages 5240–5253","venue":null,"work_id":"0d8f6502-5715-47e3-ad8f-10d73c216db9","year":2022},"citing_paper":{"arxiv_id":"2505.22096","last_updated":"2025-05-28T08:17:58Z","snapshot_observed_at":"2026-08-07T13:12:54.131841Z","submitted_at":"2025-05-28T08:17:58Z","title":"Knowledge Base Construction for Knowledge-Augmented Text-to-SQL","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T13:19:32.818994Z"},"links":{"citing_paper":"/paper/2505.22096"},"observation_digest":"sha256:d16fd0484d29d1d741990f2fabb95e069b65152482d29f2193062bec9e590fb8","observation_id":"7182237d-1397-4042-beb9-1bb7f46b8f1e","resolution":{"observed_at":"2026-08-07T13:19:36.333062Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.11517","last_updated":"2024-06-06T13:56:59Z","snapshot_observed_at":"2026-08-02T07:12:04.104343Z","submitted_at":"2024-02-18T09:10:04Z","title":"Knowledge-to-SQL: Enhancing SQL Generation with Data Expert LLM","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.11517","snapshot_observed_at":"2026-08-07T13:19:33.055710Z","title":"arXiv preprint arXiv:2402.11517","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.22096","last_updated":"2025-05-28T08:17:58Z","snapshot_observed_at":"2026-08-07T13:12:54.131841Z","submitted_at":"2025-05-28T08:17:58Z","title":"Knowledge Base Construction for Knowledge-Augmented Text-to-SQL","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T13:19:33.055710Z"},"links":{"cited_paper":"/paper/2402.11517","citing_paper":"/paper/2505.22096"},"observation_digest":"sha256:cb4d90ebd9df89998f28ce184c226d4e14508aa2573c473a59f71f6c1adced29","observation_id":"15c372f9-6f1c-4e72-9752-506d74119193","resolution":{"observed_at":"2026-08-07T13:19:33.055710Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.04088","last_updated":"2024-01-08T18:47:34Z","snapshot_observed_at":"2026-08-08T06:16:25.839566Z","submitted_at":"2024-01-08T18:47:34Z","title":"Mixtral of Experts","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.04088","snapshot_observed_at":"2026-08-07T13:19:33.140908Z","title":"arXiv preprint arXiv:2401.04088","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.22096","last_updated":"2025-05-28T08:17:58Z","snapshot_observed_at":"2026-08-07T13:12:54.131841Z","submitted_at":"2025-05-28T08:17:58Z","title":"Knowledge Base Construction for Knowledge-Augmented Text-to-SQL","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T13:19:33.140908Z"},"links":{"cited_paper":"/paper/2401.04088","citing_paper":"/paper/2505.22096"},"observation_digest":"sha256:64abd471705d1e6341cc3aeb8a3b1026af9625646bfcd2370f06b2ec9d2fb74d","observation_id":"ec5e9b5c-37d6-4881-b5ca-0a0da5d7ed5b","resolution":{"observed_at":"2026-08-07T13:19:33.140908Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.07467","last_updated":"2024-05-13T04:59:32Z","snapshot_observed_at":"2026-07-06T18:13:20.536375Z","submitted_at":"2024-05-13T04:59:32Z","title":"MCS-SQL: Leveraging Multiple Prompts and Multiple-Choice Selection For Text-to-SQL Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.07467","snapshot_observed_at":"2026-08-07T13:19:33.228541Z","title":"arXiv preprint arXiv:2405.07467","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.22096","last_updated":"2025-05-28T08:17:58Z","snapshot_observed_at":"2026-08-07T13:12:54.131841Z","submitted_at":"2025-05-28T08:17:58Z","title":"Knowledge Base Construction for Knowledge-Augmented Text-to-SQL","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T13:19:33.228541Z"},"links":{"cited_paper":"/paper/2405.07467","citing_paper":"/paper/2505.22096"},"observation_digest":"sha256:b7145c12d83a9a579bca51a7c4075431bf7d33f3f57bead90e3399ff4c37f4ce","observation_id":"c21280a1-69c2-4c12-9115-704c343f8766","resolution":{"observed_at":"2026-08-07T13:19:33.228541Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:19:35.656287Z","title":"In Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Sys- tems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16,","venue":null,"work_id":"630cedc2-28aa-4442-8fdf-b5f6f69ffc06","year":2023},"citing_paper":{"arxiv_id":"2505.22096","last_updated":"2025-05-28T08:17:58Z","snapshot_observed_at":"2026-08-07T13:12:54.131841Z","submitted_at":"2025-05-28T08:17:58Z","title":"Knowledge Base Construction for Knowledge-Augmented Text-to-SQL","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T13:19:33.296040Z"},"links":{"citing_paper":"/paper/2505.22096"},"observation_digest":"sha256:23a0d4397ace2f8dddd0de737b300998509b8ff03beec88360fa6b51b97769f2","observation_id":"eee6ceb2-01f7-4dba-a0f0-75b263d6f493","resolution":{"observed_at":"2026-08-07T13:19:35.732226Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2304.11556","last_updated":"2023-04-23T06:52:35Z","snapshot_observed_at":"2026-07-06T15:18:53.532946Z","submitted_at":"2023-04-23T06:52:35Z","title":"Divide and Prompt: Chain of Thought Prompting for Text-to-SQL","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.11556","snapshot_observed_at":"2026-08-07T13:19:33.355717Z","title":"arXiv preprint arXiv:2304.11556","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.22096","last_updated":"2025-05-28T08:17:58Z","snapshot_observed_at":"2026-08-07T13:12:54.131841Z","submitted_at":"2025-05-28T08:17:58Z","title":"Knowledge Base Construction for Knowledge-Augmented Text-to-SQL","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T13:19:33.355717Z"},"links":{"cited_paper":"/paper/2304.11556","citing_paper":"/paper/2505.22096"},"observation_digest":"sha256:e4ee3ebb896c45443f75155bc19ec28671dac017056f3865731fa2ff6d444346","observation_id":"32daeb45-e295-4f7f-89d8-30c565d9aa08","resolution":{"observed_at":"2026-08-07T13:19:33.355717Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.04324","last_updated":"2024-05-07T13:50:40Z","snapshot_observed_at":"2026-07-06T18:11:01.734775Z","submitted_at":"2024-05-07T13:50:40Z","title":"Granite Code Models: A Family of Open Foundation Models for Code Intelligence","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.04324","snapshot_observed_at":"2026-08-07T13:19:33.413242Z","title":"arXiv preprint arXiv:2405.04324","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.22096","last_updated":"2025-05-28T08:17:58Z","snapshot_observed_at":"2026-08-07T13:12:54.131841Z","submitted_at":"2025-05-28T08:17:58Z","title":"Knowledge Base Construction for Knowledge-Augmented Text-to-SQL","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T13:19:33.413242Z"},"links":{"cited_paper":"/paper/2405.04324","citing_paper":"/paper/2505.22096"},"observation_digest":"sha256:9a66eec88939d719cab7f5f3694ddfda995e7fba5c4a22e06395b3d3d4e05897","observation_id":"e24e7722-ff51-45b1-a408-3ed3768d8f42","resolution":{"observed_at":"2026-08-07T13:19:33.413242Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.02707","last_updated":"2023-06-05T08:58:39Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-06-05T08:58:39Z","title":"Orca: Progressive Learning from Complex Explanation Traces of GPT-4","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.02707","snapshot_observed_at":"2026-08-07T13:19:33.480844Z","title":"arXiv preprint arXiv:2306.02707","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.22096","last_updated":"2025-05-28T08:17:58Z","snapshot_observed_at":"2026-08-07T13:12:54.131841Z","submitted_at":"2025-05-28T08:17:58Z","title":"Knowledge Base Construction for Knowledge-Augmented Text-to-SQL","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T13:19:33.480844Z"},"links":{"cited_paper":"/paper/2306.02707","citing_paper":"/paper/2505.22096"},"observation_digest":"sha256:1f2d9ae650791e28f85e3bb60208996b7a49337df54d85002c99b5b33027d596","observation_id":"a18417c1-e999-46ff-bf8c-4c05a7efc1c1","resolution":{"observed_at":"2026-08-07T13:19:33.480844Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:19:35.576859Z","title":null,"venue":null,"work_id":"0c7ef46b-80d1-42ef-b093-26de50be6944","year":2023},"citing_paper":{"arxiv_id":"2505.22096","last_updated":"2025-05-28T08:17:58Z","snapshot_observed_at":"2026-08-07T13:12:54.131841Z","submitted_at":"2025-05-28T08:17:58Z","title":"Knowledge Base Construction for Knowledge-Augmented Text-to-SQL","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T13:19:33.540959Z"},"links":{"citing_paper":"/paper/2505.22096"},"observation_digest":"sha256:2b96752750685bcbe279221a66f37c2f0790ff3b9b2018d62cebd27087ad6253","observation_id":"fe8e6af4-031f-4a70-b9a9-5820a992d464","resolution":{"observed_at":"2026-08-07T13:19:35.592658Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-08-07T07:30:12.213965Z","submitted_at":"2023-03-15T17:15:04Z","title":"GPT-4 Technical Report","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.08774","snapshot_observed_at":"2026-08-07T13:19:33.612804Z","title":"arXiv preprint arXiv:2303.08774","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.22096","last_updated":"2025-05-28T08:17:58Z","snapshot_observed_at":"2026-08-07T13:12:54.131841Z","submitted_at":"2025-05-28T08:17:58Z","title":"Knowledge Base Construction for Knowledge-Augmented Text-to-SQL","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T13:19:33.612804Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2505.22096"},"observation_digest":"sha256:77889d0a4118ccee87056b7a30d04ef74156bc896ac64995d1002d8b5b880c4d","observation_id":"1a9edcf3-59a1-44fc-8899-51a1b2971d10","resolution":{"observed_at":"2026-08-07T13:19:33.612804Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:19:35.503162Z","title":"In Advances in Neural Information Processing Systems 36: Annual Confer- ence on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16,","venue":null,"work_id":"0a778660-b06e-413e-8063-a53824d7b19c","year":2023},"citing_paper":{"arxiv_id":"2505.22096","last_updated":"2025-05-28T08:17:58Z","snapshot_observed_at":"2026-08-07T13:12:54.131841Z","submitted_at":"2025-05-28T08:17:58Z","title":"Knowledge Base Construction for Knowledge-Augmented Text-to-SQL","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T13:19:33.675919Z"},"links":{"citing_paper":"/paper/2505.22096"},"observation_digest":"sha256:5cc16f63e3cd747d786ebbc743f1e60a0aa9e39886e6fdc485eda1b12d38668f","observation_id":"7bd5dab4-0049-46df-ac19-e48f448e548d","resolution":{"observed_at":"2026-08-07T13:19:35.562996Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2204.00498","last_updated":"2022-03-15T17:23:53Z","snapshot_observed_at":"2026-07-06T12:55:45.766333Z","submitted_at":"2022-03-15T17:23:53Z","title":"Evaluating the Text-to-SQL Capabilities of Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.00498","snapshot_observed_at":"2026-08-07T13:19:33.724722Z","title":"arXiv preprint arXiv:2204.00498","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.22096","last_updated":"2025-05-28T08:17:58Z","snapshot_observed_at":"2026-08-07T13:12:54.131841Z","submitted_at":"2025-05-28T08:17:58Z","title":"Knowledge Base Construction for Knowledge-Augmented Text-to-SQL","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T13:19:33.724722Z"},"links":{"cited_paper":"/paper/2204.00498","citing_paper":"/paper/2505.22096"},"observation_digest":"sha256:1fe9c28c5827537bf1e9eb3d0c94f4d5d2dfc35bf08ec9caf71586b58d0472b8","observation_id":"658d5135-92e4-48ff-8857-4d3e09a3b923","resolution":{"observed_at":"2026-08-07T13:19:33.724722Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:19:35.370088Z","title":"In Advances in Neural Information Processing Systems 33: An- nual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual","venue":null,"work_id":"346f8813-eefc-4b5f-b531-2c4dfa514974","year":2020},"citing_paper":{"arxiv_id":"2505.22096","last_updated":"2025-05-28T08:17:58Z","snapshot_observed_at":"2026-08-07T13:12:54.131841Z","submitted_at":"2025-05-28T08:17:58Z","title":"Knowledge Base Construction for Knowledge-Augmented Text-to-SQL","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T13:19:33.773556Z"},"links":{"citing_paper":"/paper/2505.22096"},"observation_digest":"sha256:6ade2f0b8286800ac604f5dd46ff21ce641eba9881fd096ba4e5367a52c2d3c9","observation_id":"715d600d-ba0d-4346-b6ed-a9a2dedbea1f","resolution":{"observed_at":"2026-08-07T13:19:35.424835Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.01081","last_updated":"2024-04-29T18:55:34Z","snapshot_observed_at":"2026-07-06T17:38:30.401240Z","submitted_at":"2024-03-02T03:48:37Z","title":"LAB: Large-Scale Alignment for ChatBots","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.01081","snapshot_observed_at":"2026-08-07T13:19:33.832836Z","title":"arXiv preprint arXiv:2403.01081","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.22096","last_updated":"2025-05-28T08:17:58Z","snapshot_observed_at":"2026-08-07T13:12:54.131841Z","submitted_at":"2025-05-28T08:17:58Z","title":"Knowledge Base Construction for Knowledge-Augmented Text-to-SQL","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T13:19:33.832836Z"},"links":{"cited_paper":"/paper/2403.01081","citing_paper":"/paper/2505.22096"},"observation_digest":"sha256:7e2185d366cb7a662bea0272aee30db3d8c839dc4ba4b75b1e0ea7f37d45e5f7","observation_id":"da06e35a-9c0a-47a4-8fee-78e10ac8ea77","resolution":{"observed_at":"2026-08-07T13:19:33.832836Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:19:35.233213Z","title":"In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, EMNLP 2023, Singapore, De- cember 6-10, 2023, pages 5376–5393","venue":null,"work_id":"55f77268-b221-4593-a4d7-f5720479fd49","year":2023},"citing_paper":{"arxiv_id":"2505.22096","last_updated":"2025-05-28T08:17:58Z","snapshot_observed_at":"2026-08-07T13:12:54.131841Z","submitted_at":"2025-05-28T08:17:58Z","title":"Knowledge Base Construction for Knowledge-Augmented Text-to-SQL","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T13:19:33.868697Z"},"links":{"citing_paper":"/paper/2505.22096"},"observation_digest":"sha256:1125eea68a42ab621d3bcc730aca0eb3442e4a327cdc8da5abcd6d1a2baca55f","observation_id":"4b460706-9cb2-4166-967c-ac9fb15a5552","resolution":{"observed_at":"2026-08-07T13:19:35.298731Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:19:35.135347Z","title":"In Find- ings of the Association for Computational Linguis- tics: EMNLP 2023, Singapore, December 6-10, 2023, pages 6432–6443","venue":null,"work_id":"3a5f3cfc-eefd-4f99-a430-8122694335b7","year":2023},"citing_paper":{"arxiv_id":"2505.22096","last_updated":"2025-05-28T08:17:58Z","snapshot_observed_at":"2026-08-07T13:12:54.131841Z","submitted_at":"2025-05-28T08:17:58Z","title":"Knowledge Base Construction for Knowledge-Augmented Text-to-SQL","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T13:19:33.945759Z"},"links":{"citing_paper":"/paper/2505.22096"},"observation_digest":"sha256:65e94c748525afbecb4e5e96e581a85b60361332f45428b048113170cdb72169","observation_id":"1be833f1-ee2a-4cbe-804d-5610144589e0","resolution":{"observed_at":"2026-08-07T13:19:35.179363Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:19:34.928365Z","title":"Yizhong Wang, Yeganeh Kordi, Swaroop Mishra, Alisa Liu, Noah A","venue":null,"work_id":"42f56a32-33fd-428e-834f-4b4b922c60da","year":2023},"citing_paper":{"arxiv_id":"2505.22096","last_updated":"2025-05-28T08:17:58Z","snapshot_observed_at":"2026-08-07T13:12:54.131841Z","submitted_at":"2025-05-28T08:17:58Z","title":"Knowledge Base Construction for Knowledge-Augmented Text-to-SQL","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T13:19:34.109444Z"},"links":{"citing_paper":"/paper/2505.22096"},"observation_digest":"sha256:8353ca60e12fea62f015e7e7b802799147ed5393d753c7dab3b2e5100d3ef2af","observation_id":"9b84d7ef-8c68-4e53-9985-a69c95abfbf6","resolution":{"observed_at":"2026-08-07T13:19:35.025110Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:19:34.220639Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.22096","last_updated":"2025-05-28T08:17:58Z","snapshot_observed_at":"2026-08-07T13:12:54.131841Z","submitted_at":"2025-05-28T08:17:58Z","title":"Knowledge Base Construction for Knowledge-Augmented Text-to-SQL","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T13:19:34.220639Z"},"links":{"citing_paper":"/paper/2505.22096"},"observation_digest":"sha256:dff94d5b30436e6fda722903eb90fe63a1466baa3034d2c9635f7d6bba794259","observation_id":"2e1a8187-234a-4ff1-b6a6-a6b5f9bc090a","resolution":{"observed_at":"2026-08-07T13:19:34.220639Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.12244","last_updated":"2025-05-27T06:49:09Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-04-24T16:31:06Z","title":"WizardLM: Empowering large pre-trained language models to follow complex instructions","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.12244","snapshot_observed_at":"2026-08-07T13:19:34.267947Z","title":"arXiv preprint arXiv:2304.12244","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.22096","last_updated":"2025-05-28T08:17:58Z","snapshot_observed_at":"2026-08-07T13:12:54.131841Z","submitted_at":"2025-05-28T08:17:58Z","title":"Knowledge Base Construction for Knowledge-Augmented Text-to-SQL","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T13:19:34.267947Z"},"links":{"cited_paper":"/paper/2304.12244","citing_paper":"/paper/2505.22096"},"observation_digest":"sha256:37a7e7a6a02c087512a0038c0bdbc1d48e140a8605e657c8eff9c71b59260f27","observation_id":"a9fccec0-a378-4524-8ff3-1375d18aefcd","resolution":{"observed_at":"2026-08-07T13:19:34.267947Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:19:34.828952Z","title":"In Proceed- ings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31 - November 4, 2018, pages 3911–3921","venue":null,"work_id":"f12be2b7-4e83-4acf-92a0-9d287a028fb9","year":2018},"citing_paper":{"arxiv_id":"2505.22096","last_updated":"2025-05-28T08:17:58Z","snapshot_observed_at":"2026-08-07T13:12:54.131841Z","submitted_at":"2025-05-28T08:17:58Z","title":"Knowledge Base Construction for Knowledge-Augmented Text-to-SQL","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T13:19:34.373109Z"},"links":{"citing_paper":"/paper/2505.22096"},"observation_digest":"sha256:6ef7849e2813dac5a708709fa8998cacb2d154aac28585fe1241a07e6ba28414","observation_id":"ca8d54e0-caa2-4451-b1c2-78820e8016b5","resolution":{"observed_at":"2026-08-07T13:19:34.876361Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:19:34.706792Z","title":null,"venue":null,"work_id":"61173061-838c-41c8-a17d-5109e5e98936","year":1996},"citing_paper":{"arxiv_id":"2505.22096","last_updated":"2025-05-28T08:17:58Z","snapshot_observed_at":"2026-08-07T13:12:54.131841Z","submitted_at":"2025-05-28T08:17:58Z","title":"Knowledge Base Construction for Knowledge-Augmented Text-to-SQL","version":1},"reference_index":1996,"source":"pdf_text","source_observed_at":"2026-08-07T13:19:34.441277Z"},"links":{"citing_paper":"/paper/2505.22096"},"observation_digest":"sha256:7eadb925dc0c47eb17dc392196fa5bef34579e7f63c0440a0113e2cad5846eb0","observation_id":"41f3c71e-ba98-42fd-a9f3-f6ab89aaa69d","resolution":{"observed_at":"2026-08-07T13:19:34.749403Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.11242","last_updated":"2025-03-18T02:12:21Z","snapshot_observed_at":"2026-07-06T17:04:37.751364Z","submitted_at":"2023-12-18T14:40:20Z","title":"MAC-SQL: A Multi-Agent Collaborative Framework for Text-to-SQL","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.11242","snapshot_observed_at":"2026-08-07T13:19:34.017622Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.22096","last_updated":"2025-05-28T08:17:58Z","snapshot_observed_at":"2026-08-07T13:12:54.131841Z","submitted_at":"2025-05-28T08:17:58Z","title":"Knowledge Base Construction for Knowledge-Augmented Text-to-SQL","version":1},"reference_index":2014,"source":"pdf_text","source_observed_at":"2026-08-07T13:19:34.017622Z"},"links":{"cited_paper":"/paper/2312.11242","citing_paper":"/paper/2505.22096"},"observation_digest":"sha256:801d9d0bc4ac1a22153775dd207bc1a08bf2dfb3fbc999907da1b5c0fb0bd740","observation_id":"8a7c2204-858d-45e2-83d1-d77e881adbc8","resolution":{"observed_at":"2026-08-07T13:19:34.017622Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1711.04436","last_updated":"2017-11-13T06:41:29Z","snapshot_observed_at":"2026-07-06T06:09:05.613678Z","submitted_at":"2017-11-13T06:41:29Z","title":"SQLNet: Generating Structured Queries From Natural Language Without Reinforcement Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1711.04436","snapshot_observed_at":"2026-08-07T13:19:34.311722Z","title":"arXiv preprint arXiv:1711.04436","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.22096","last_updated":"2025-05-28T08:17:58Z","snapshot_observed_at":"2026-08-07T13:12:54.131841Z","submitted_at":"2025-05-28T08:17:58Z","title":"Knowledge Base Construction for Knowledge-Augmented Text-to-SQL","version":1},"reference_index":2017,"source":"pdf_text","source_observed_at":"2026-08-07T13:19:34.311722Z"},"links":{"cited_paper":"/paper/1711.04436","citing_paper":"/paper/2505.22096"},"observation_digest":"sha256:7a9593289b190e0d506f43d16fbfc57f5481f799b20430c7abb8c7c67b097b6a","observation_id":"ff88d62f-47db-4860-ba7d-43e6c4387c3c","resolution":{"observed_at":"2026-08-07T13:19:34.311722Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:19:36.718216Z","title":"In Proceedings of the Twenty- Seventh International Joint Conference on Artificial Intelligence, IJCAI 2018, July 13-19, 2018, Stock- holm, Sweden, pages 3977–3983","venue":null,"work_id":"7105ad9d-aeb7-4d07-8d94-1cad3f0c5c85","year":2018},"citing_paper":{"arxiv_id":"2505.22096","last_updated":"2025-05-28T08:17:58Z","snapshot_observed_at":"2026-08-07T13:12:54.131841Z","submitted_at":"2025-05-28T08:17:58Z","title":"Knowledge Base Construction for Knowledge-Augmented Text-to-SQL","version":1},"reference_index":2018,"source":"pdf_text","source_observed_at":"2026-08-07T13:19:32.456257Z"},"links":{"citing_paper":"/paper/2505.22096"},"observation_digest":"sha256:afd7391d3c2327160ddffd2d93bcd53a4c819c68c0601fca5d0389417dde8608","observation_id":"dd4c4fb2-57dd-4c45-8702-bc971d901c79","resolution":{"observed_at":"2026-08-07T13:19:36.832488Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:19:36.435923Z","title":null,"venue":null,"work_id":"c61cde15-d02c-4d59-afc5-9bbc2b8966cc","year":2019},"citing_paper":{"arxiv_id":"2505.22096","last_updated":"2025-05-28T08:17:58Z","snapshot_observed_at":"2026-08-07T13:12:54.131841Z","submitted_at":"2025-05-28T08:17:58Z","title":"Knowledge Base Construction for Knowledge-Augmented Text-to-SQL","version":1},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-07T13:19:32.679570Z"},"links":{"citing_paper":"/paper/2505.22096"},"observation_digest":"sha256:3b11fc5e16bd571c0c6ef91b31ccd7daee51f9e666cb8499517fb4a0a51503d6","observation_id":"0db4b45b-ac8b-4094-ad82-16a4eb1515c9","resolution":{"observed_at":"2026-08-07T13:19:36.544954Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:19:35.837165Z","title":"In Proceedings of the 2020 Conference on Empirical Methods in Nat- ural Language Processing, EMNLP 2020, Online, November 16-20, 2020, pages 6769–6781","venue":null,"work_id":"588e2130-9cd5-4033-b493-b9bf54531716","year":2020},"citing_paper":{"arxiv_id":"2505.22096","last_updated":"2025-05-28T08:17:58Z","snapshot_observed_at":"2026-08-07T13:12:54.131841Z","submitted_at":"2025-05-28T08:17:58Z","title":"Knowledge Base Construction for Knowledge-Augmented Text-to-SQL","version":1},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-07T13:19:33.195583Z"},"links":{"citing_paper":"/paper/2505.22096"},"observation_digest":"sha256:fbd2ae2ec9f9f1b01cd17b9cd8369a61ed0fc50e2d67f344f117ab41c07f2aad","observation_id":"cd363df1-51d7-4b19-bd8e-67b12ea0b6ed","resolution":{"observed_at":"2026-08-07T13:19:35.903118Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:19:35.980491Z","title":"In SIGIR ’21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event, Canada, July 11-15, 2021 , pages 113–122","venue":null,"work_id":"836bdae9-1c72-4012-9b5f-3f91f20d98d8","year":2021},"citing_paper":{"arxiv_id":"2505.22096","last_updated":"2025-05-28T08:17:58Z","snapshot_observed_at":"2026-08-07T13:12:54.131841Z","submitted_at":"2025-05-28T08:17:58Z","title":"Knowledge Base Construction for Knowledge-Augmented Text-to-SQL","version":1},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-07T13:19:32.968192Z"},"links":{"citing_paper":"/paper/2505.22096"},"observation_digest":"sha256:570b899fc1f5d05d5cc1d46523e0ee6845de46fd676bfd3573f69cc7d703e950","observation_id":"8a00be90-5619-4aba-b82d-34c0f86ab4f8","resolution":{"observed_at":"2026-08-07T13:19:36.128829Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:19:36.988906Z","title":null,"venue":null,"work_id":"5905ec17-fc1b-4414-a42a-eabf40576a89","year":2022},"citing_paper":{"arxiv_id":"2505.22096","last_updated":"2025-05-28T08:17:58Z","snapshot_observed_at":"2026-08-07T13:12:54.131841Z","submitted_at":"2025-05-28T08:17:58Z","title":"Knowledge Base Construction for Knowledge-Augmented Text-to-SQL","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-07T13:19:32.349776Z"},"links":{"citing_paper":"/paper/2505.22096"},"observation_digest":"sha256:181611aab3c5955ad043dbcc764fcd44c9cb72e80dcf316bd4e538845b7c9a24","observation_id":"b09c0b9b-ca8d-4f35-ab7b-ffb0606f0f5f","resolution":{"observed_at":"2026-08-07T13:19:37.074111Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.11805","last_updated":"2025-05-09T21:04:06Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-12-19T02:39:27Z","title":"Gemini: A Family of Highly Capable Multimodal Models","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.11805","snapshot_observed_at":"2026-08-07T13:19:32.399770Z","title":"arXiv preprint arXiv:2312.11805","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.22096","last_updated":"2025-05-28T08:17:58Z","snapshot_observed_at":"2026-08-07T13:12:54.131841Z","submitted_at":"2025-05-28T08:17:58Z","title":"Knowledge Base Construction for Knowledge-Augmented Text-to-SQL","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-07T13:19:32.399770Z"},"links":{"cited_paper":"/paper/2312.11805","citing_paper":"/paper/2505.22096"},"observation_digest":"sha256:f0b8bf88bb701a806255436ba2fd2512c3cdd88bb9b132952b2bd5f35eb6d4b7","observation_id":"31739589-05f6-4d37-8bff-4e296e553a42","resolution":{"observed_at":"2026-08-07T13:19:32.399770Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.08281","last_updated":"2025-10-23T09:36:08Z","snapshot_observed_at":"2026-07-31T05:45:37.385210Z","submitted_at":"2024-01-16T11:12:36Z","title":"The Faiss library","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.08281","snapshot_observed_at":"2026-08-07T13:19:32.917397Z","title":"arXiv preprint arXiv:2401.08281","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.22096","last_updated":"2025-05-28T08:17:58Z","snapshot_observed_at":"2026-08-07T13:12:54.131841Z","submitted_at":"2025-05-28T08:17:58Z","title":"Knowledge Base Construction for Knowledge-Augmented Text-to-SQL","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-07T13:19:32.917397Z"},"links":{"cited_paper":"/paper/2401.08281","citing_paper":"/paper/2505.22096"},"observation_digest":"sha256:b4d78f066540a48d6d7be6dab86c2f87ed390d5cc2c41c2c381c3076a78eac76","observation_id":"c38e2cb1-8c0a-49d1-b14e-79c0b6941b95","resolution":{"observed_at":"2026-08-07T13:19:32.917397Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2505.22096","last_updated":"2025-05-28T08:17:58Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-07T13:12:54.131841Z","submitted_at":"2025-05-28T08:17:58Z","title":"Knowledge Base Construction for Knowledge-Augmented Text-to-SQL"},"reference_resolution":{"displayed":32,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":21,"verified_exact":0,"verified_fuzzy":11},"total_outbound_references":32},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2505.22096."}