{"as_of":"2026-08-08T02:50:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:9b8b4d28cc25f66e95f41b9bd06cdd4ffbf2bbbfa22e5df170adaf05214d9741","coverage":[{"denominator":16,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":16,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-02T05:38:05.945559Z","state":"measured"},{"denominator":16,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":16,"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/2607.13311/citation-record","integrity":"/paper/2607.13311/integrity","json":"/paper/2607.13311/citation-record.json","paper":"/paper/2607.13311"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T05:38:05.385914Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.13311","last_updated":"2026-07-14T22:31:55Z","snapshot_observed_at":"2026-08-03T11:02:27.846136Z","submitted_at":"2026-07-14T22:31:55Z","title":"Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-02T05:38:05.385914Z"},"links":{"citing_paper":"/paper/2607.13311"},"observation_digest":"sha256:83f76d487448207425b06081e83166f36f124e03612d45f1ae10db7ee486711f","observation_id":"b97c48a2-1b0b-4c61-800b-11cbc25b00ed","resolution":{"observed_at":"2026-08-02T05:38:05.385914Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T05:38:05.487691Z","title":"https://github.com/bird- bench/livesqlbench","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.13311","last_updated":"2026-07-14T22:31:55Z","snapshot_observed_at":"2026-08-03T11:02:27.846136Z","submitted_at":"2026-07-14T22:31:55Z","title":"Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-02T05:38:05.487691Z"},"links":{"citing_paper":"/paper/2607.13311"},"observation_digest":"sha256:11b3c11d528b0fb23a25f370f1c000d4ebf60c2af8859f2639a2f94c7f6b8932","observation_id":"7cca6b27-ae8e-46cd-bb03-f18255b5e128","resolution":{"observed_at":"2026-08-02T05:38:05.487691Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T05:38:05.612402Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.13311","last_updated":"2026-07-14T22:31:55Z","snapshot_observed_at":"2026-08-03T11:02:27.846136Z","submitted_at":"2026-07-14T22:31:55Z","title":"Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-02T05:38:05.612402Z"},"links":{"citing_paper":"/paper/2607.13311"},"observation_digest":"sha256:cd83db880a738ab355cd3b52fb1932698ae002949858da949c7ffb89b92194ae","observation_id":"a6403739-2376-4f5c-ae14-35090870a4e0","resolution":{"observed_at":"2026-08-02T05:38:05.612402Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2212.03533","last_updated":"2024-02-22T06:21:51Z","snapshot_observed_at":"2026-07-06T14:27:46.217000Z","submitted_at":"2022-12-07T09:25:54Z","title":"Text Embeddings by Weakly-Supervised Contrastive Pre-training","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.03533","snapshot_observed_at":"2026-08-02T05:38:05.736898Z","title":"Shitao Xiao, Zheng Liu, Peitian Zhang, Niklas Muen- nighoff, Defu Lian, and Jian-Yun Nie","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.13311","last_updated":"2026-07-14T22:31:55Z","snapshot_observed_at":"2026-08-03T11:02:27.846136Z","submitted_at":"2026-07-14T22:31:55Z","title":"Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-02T05:38:05.736898Z"},"links":{"cited_paper":"/paper/2212.03533","citing_paper":"/paper/2607.13311"},"observation_digest":"sha256:f78cb36afd4ed2b9ee3d87d8ce9490a384a7442dcbc4396d2016dc11f9341a2c","observation_id":"20973b10-dad6-43f0-83df-dbdce53ccdf6","resolution":{"observed_at":"2026-08-02T05:38:05.736898Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2007.00808","last_updated":"2020-10-20T22:17:19Z","snapshot_observed_at":"2026-08-06T15:45:53.027828Z","submitted_at":"2020-07-01T23:15:56Z","title":"Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2007.00808","snapshot_observed_at":"2026-08-02T05:38:05.814131Z","title":"Preprint, arXiv:2007.00808","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2607.13311","last_updated":"2026-07-14T22:31:55Z","snapshot_observed_at":"2026-08-03T11:02:27.846136Z","submitted_at":"2026-07-14T22:31:55Z","title":"Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-02T05:38:05.814131Z"},"links":{"cited_paper":"/paper/2007.00808","citing_paper":"/paper/2607.13311"},"observation_digest":"sha256:991794de925f9ed52043628cea4dec92820bd31624cc6a41470a452bdf13bfdf","observation_id":"91db9932-639d-42d0-90b9-31cf829bb559","resolution":{"observed_at":"2026-08-02T05:38:05.814131Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.05176","last_updated":"2025-06-11T02:54:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-05T15:49:48Z","title":"Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.05176","snapshot_observed_at":"2026-08-02T05:38:05.904886Z","title":"Preprint, arXiv:2506.05176","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.13311","last_updated":"2026-07-14T22:31:55Z","snapshot_observed_at":"2026-08-03T11:02:27.846136Z","submitted_at":"2026-07-14T22:31:55Z","title":"Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-02T05:38:05.904886Z"},"links":{"cited_paper":"/paper/2506.05176","citing_paper":"/paper/2607.13311"},"observation_digest":"sha256:e3ae25db1fd87d8444a7889276ed26c8ba6aa4a31bf30d6bbd9ba9cc2ae829e9","observation_id":"18ed0219-7eec-4942-ab63-180d579b4f99","resolution":{"observed_at":"2026-08-02T05:38:05.904886Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1709.00103","last_updated":"2017-11-09T23:06:14Z","snapshot_observed_at":"2026-08-03T05:45:09.122112Z","submitted_at":"2017-08-31T23:12:15Z","title":"Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning","version":7},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1709.00103","snapshot_observed_at":"2026-08-02T05:38:05.945559Z","title":"query\":","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.13311","last_updated":"2026-07-14T22:31:55Z","snapshot_observed_at":"2026-08-03T11:02:27.846136Z","submitted_at":"2026-07-14T22:31:55Z","title":"Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval","version":1},"reference_index":2017,"source":"pdf_text","source_observed_at":"2026-08-02T05:38:05.945559Z"},"links":{"cited_paper":"/paper/1709.00103","citing_paper":"/paper/2607.13311"},"observation_digest":"sha256:cd69a628d40f3a020de48ad5453cccb1a586aaceaec87f5f20cd771ec8529580","observation_id":"03037b5a-949b-493c-9915-ee88d6083760","resolution":{"observed_at":"2026-08-02T05:38:05.945559Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T05:38:05.866302Z","title":"InProceedings of the 2018 Conference on Empirical Methods in Natural Lan- guage Processing, pages 3911–3921, Brussels, Bel- gium","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.13311","last_updated":"2026-07-14T22:31:55Z","snapshot_observed_at":"2026-08-03T11:02:27.846136Z","submitted_at":"2026-07-14T22:31:55Z","title":"Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval","version":1},"reference_index":2018,"source":"pdf_text","source_observed_at":"2026-08-02T05:38:05.866302Z"},"links":{"citing_paper":"/paper/2607.13311"},"observation_digest":"sha256:0f964685c69f38811fb422984c41cf956300ab02f92e7e1d9121aff689aa622c","observation_id":"8fa2e5c8-7c6c-4631-b9dd-30e964d64e9b","resolution":{"observed_at":"2026-08-02T05:38:05.866302Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1904.08375","last_updated":"2019-09-25T00:40:54Z","snapshot_observed_at":"2026-08-05T06:27:23.978783Z","submitted_at":"2019-04-17T17:20:14Z","title":"Document Expansion by Query Prediction","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1904.08375","snapshot_observed_at":"2026-08-02T05:38:05.182424Z","title":"Mohammadreza Pourreza and Davood Rafiei","venue":null,"work_id":null,"year":1904},"citing_paper":{"arxiv_id":"2607.13311","last_updated":"2026-07-14T22:31:55Z","snapshot_observed_at":"2026-08-03T11:02:27.846136Z","submitted_at":"2026-07-14T22:31:55Z","title":"Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval","version":1},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-02T05:38:05.182424Z"},"links":{"cited_paper":"/paper/1904.08375","citing_paper":"/paper/2607.13311"},"observation_digest":"sha256:73fcb872429ea84661b8c0ab6d2cdb1c1b6c23d0335ddfb1b74df7f0dba2eb3f","observation_id":"3160c85f-7f22-492d-b237-ba29d3c34e23","resolution":{"observed_at":"2026-08-02T05:38:05.182424Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T05:38:04.484088Z","title":"InProceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 6769–6781, Online","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.13311","last_updated":"2026-07-14T22:31:55Z","snapshot_observed_at":"2026-08-03T11:02:27.846136Z","submitted_at":"2026-07-14T22:31:55Z","title":"Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval","version":1},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-02T05:38:04.484088Z"},"links":{"citing_paper":"/paper/2607.13311"},"observation_digest":"sha256:68667fadc49139b440f881954c912e08a7f07a3da41090062912f1839ce0e739","observation_id":"65b415a1-9783-4e60-b0c3-ece85eb959c4","resolution":{"observed_at":"2026-08-02T05:38:04.484088Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T05:38:05.279799Z","title":"InProceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Hu- man Language Technologies, pages 5835–5847, On- line","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.13311","last_updated":"2026-07-14T22:31:55Z","snapshot_observed_at":"2026-08-03T11:02:27.846136Z","submitted_at":"2026-07-14T22:31:55Z","title":"Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval","version":1},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-02T05:38:05.279799Z"},"links":{"citing_paper":"/paper/2607.13311"},"observation_digest":"sha256:cea588ff2c56e550d606cfef4bba2dac477c8ac97e566c25c9be1b4495ca8cd6","observation_id":"a2ca9db2-b0db-4756-ac2d-5693ca967bff","resolution":{"observed_at":"2026-08-02T05:38:05.279799Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2209.11755","last_updated":"2022-09-23T17:59:06Z","snapshot_observed_at":"2026-07-06T13:55:41.552052Z","submitted_at":"2022-09-23T17:59:06Z","title":"Promptagator: Few-shot Dense Retrieval From 8 Examples","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.11755","snapshot_observed_at":"2026-08-02T05:38:04.339592Z","title":"Dawei Gao, Haibin Wang, Yaliang Li, Xiuyu Sun, Yichen Qian, Bolin Ding, and Jingren Zhou","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.13311","last_updated":"2026-07-14T22:31:55Z","snapshot_observed_at":"2026-08-03T11:02:27.846136Z","submitted_at":"2026-07-14T22:31:55Z","title":"Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-02T05:38:04.339592Z"},"links":{"cited_paper":"/paper/2209.11755","citing_paper":"/paper/2607.13311"},"observation_digest":"sha256:f2606358369f27ad058f5d0880e37a3406e21a7a11a8cf5d11b6d0f51512745e","observation_id":"20443763-e8d5-4780-9904-8976e1d8cff8","resolution":{"observed_at":"2026-08-02T05:38:04.339592Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T05:38:05.017323Z","title":"InProceedings of the 17th Conference of the European Chapter of the Association for Com- putational Linguistics, pages 2014–2037, Dubrovnik, Croatia","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2607.13311","last_updated":"2026-07-14T22:31:55Z","snapshot_observed_at":"2026-08-03T11:02:27.846136Z","submitted_at":"2026-07-14T22:31:55Z","title":"Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-02T05:38:05.017323Z"},"links":{"citing_paper":"/paper/2607.13311"},"observation_digest":"sha256:65a257b92044ad8222e5b811f6b4b0439f681c8b4d6635f6ee477615b50cd405","observation_id":"2b2cdd30-afb7-491d-b635-210891d22f95","resolution":{"observed_at":"2026-08-02T05:38:05.017323Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.05374","last_updated":"2024-05-08T19:05:18Z","snapshot_observed_at":"2026-07-06T18:11:48.858911Z","submitted_at":"2024-05-08T19:05:18Z","title":"Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.05374","snapshot_observed_at":"2026-08-02T05:38:04.815422Z","title":"Niklas Muennighoff, Nouamane Tazi, Loic Magne, and Nils Reimers","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.13311","last_updated":"2026-07-14T22:31:55Z","snapshot_observed_at":"2026-08-03T11:02:27.846136Z","submitted_at":"2026-07-14T22:31:55Z","title":"Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-02T05:38:04.815422Z"},"links":{"cited_paper":"/paper/2405.05374","citing_paper":"/paper/2607.13311"},"observation_digest":"sha256:ba068e317950daae14043259e515c8ce17d787db70b112e11690f81ef9b777e5","observation_id":"8306f99a-2e4a-47ba-9cec-5bca3c7661f1","resolution":{"observed_at":"2026-08-02T05:38:04.815422Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.12644","last_updated":"2025-08-08T04:35:26Z","snapshot_observed_at":"2026-07-06T19:52:42.231424Z","submitted_at":"2024-11-19T16:54:45Z","title":"CodeXEmbed: A Generalist Embedding Model Family for Multiligual and Multi-task Code Retrieval","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.12644","snapshot_observed_at":"2026-08-02T05:38:04.668615Z","title":"Preprint, arXiv:2411.12644","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.13311","last_updated":"2026-07-14T22:31:55Z","snapshot_observed_at":"2026-08-03T11:02:27.846136Z","submitted_at":"2026-07-14T22:31:55Z","title":"Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval","version":1},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-02T05:38:04.668615Z"},"links":{"cited_paper":"/paper/2411.12644","citing_paper":"/paper/2607.13311"},"observation_digest":"sha256:a31a39862849e02d261244cdc76f80944b3ef1786a67b2911aa376e5ef15d2fb","observation_id":"79d1500f-94e3-4de7-ad4c-355582051aed","resolution":{"observed_at":"2026-08-02T05:38:04.668615Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.02038","last_updated":"2026-05-13T15:02:07Z","snapshot_observed_at":"2026-07-06T19:09:50.836734Z","submitted_at":"2024-09-03T16:37:45Z","title":"BEAVER: An Enterprise Benchmark for Text-to-SQL","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.02038","snapshot_observed_at":"2026-08-02T05:38:04.253210Z","title":"Zhuyun Dai, Vincent Y","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.13311","last_updated":"2026-07-14T22:31:55Z","snapshot_observed_at":"2026-08-03T11:02:27.846136Z","submitted_at":"2026-07-14T22:31:55Z","title":"Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval","version":1},"reference_index":2026,"source":"pdf_text","source_observed_at":"2026-08-02T05:38:04.253210Z"},"links":{"cited_paper":"/paper/2409.02038","citing_paper":"/paper/2607.13311"},"observation_digest":"sha256:e2ab3c5de518e136cfef3ba305c8a8dd2ce15851ec32708057b4af759e51425e","observation_id":"e6389750-bf39-487e-9f4d-d90c35597b9b","resolution":{"observed_at":"2026-08-02T05:38:04.253210Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.13311","last_updated":"2026-07-14T22:31:55Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-03T11:02:27.846136Z","submitted_at":"2026-07-14T22:31:55Z","title":"Finding the Right Tables and Columns: A Benchmark and Corpus-Adaptive Embeddings for SQL Schema Retrieval"},"reference_resolution":{"displayed":16,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":16,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":16},"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 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2607.13311."}