{"as_of":"2026-08-09T21:02:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:8a16809a4c8965f04dd29b4709d575475707bcecfcf2b1a2993d2194c26e131a","coverage":[{"denominator":28,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":28,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T04:54:40.025942Z","state":"measured"},{"denominator":28,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":28,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+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/2506.09359/citation-record","integrity":"/paper/2506.09359/integrity","json":"/paper/2506.09359/citation-record.json","paper":"/paper/2506.09359"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:54:39.916577Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.09359","last_updated":"2025-06-11T03:16:39Z","snapshot_observed_at":"2026-08-07T04:47:53.823224Z","submitted_at":"2025-06-11T03:16:39Z","title":"Taming SQL Complexity: LLM-Based Equivalence Evaluation for Text-to-SQL","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:39.916577Z"},"links":{"citing_paper":"/paper/2506.09359"},"observation_digest":"sha256:8fd3effdd9f2667869efd4ac13538af1c35a1ba5b37860bfadd836d44d482e80","observation_id":"a6c36653-877b-4cab-969d-f47ab065781f","resolution":{"observed_at":"2026-08-07T04:54:39.916577Z","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":"2026-08-07T04:54:40.330909Z","title":"Open-sourcing sql eval: Making benchmarking easier for sql generation models, November 2024","venue":null,"work_id":"b80aa16e-4abb-4a83-9cd6-4448edb6b4af","year":2024},"citing_paper":{"arxiv_id":"2506.09359","last_updated":"2025-06-11T03:16:39Z","snapshot_observed_at":"2026-08-07T04:47:53.823224Z","submitted_at":"2025-06-11T03:16:39Z","title":"Taming SQL Complexity: LLM-Based Equivalence Evaluation for Text-to-SQL","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:39.921580Z"},"links":{"citing_paper":"/paper/2506.09359"},"observation_digest":"sha256:30e2f38d2720e2dd9a1e4833c83e3f8e27db194618e407a7126eaf332edbd5ac","observation_id":"f6042df2-c913-429c-ae53-4b8120a88806","resolution":{"observed_at":"2026-08-07T04:54:40.334768Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.07313","last_updated":"2025-06-16T20:19:19Z","snapshot_observed_at":"2026-08-09T12:11:53.394626Z","submitted_at":"2024-07-10T02:20:19Z","title":"ETM: Modern Insights into Perspective on Text-to-SQL Evaluation in the Age of Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.07313","snapshot_observed_at":"2026-08-07T04:54:39.925206Z","title":"G., Kandikonda, Y","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.09359","last_updated":"2025-06-11T03:16:39Z","snapshot_observed_at":"2026-08-07T04:47:53.823224Z","submitted_at":"2025-06-11T03:16:39Z","title":"Taming SQL Complexity: LLM-Based Equivalence Evaluation for Text-to-SQL","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:39.925206Z"},"links":{"cited_paper":"/paper/2407.07313","citing_paper":"/paper/2506.09359"},"observation_digest":"sha256:ffddbe1e8ab7def826bae011bd571f25bc873554e3b82ed6212a9212a7a4e663","observation_id":"093beab7-0db2-4ca7-b1e8-58a3e06f081d","resolution":{"observed_at":"2026-08-07T04:54:39.925206Z","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":"2026-08-07T04:54:40.321315Z","title":"and Lee, H.-y","venue":null,"work_id":"51b7db0d-76e2-4140-854e-eab71b12b36f","year":2023},"citing_paper":{"arxiv_id":"2506.09359","last_updated":"2025-06-11T03:16:39Z","snapshot_observed_at":"2026-08-07T04:47:53.823224Z","submitted_at":"2025-06-11T03:16:39Z","title":"Taming SQL Complexity: LLM-Based Equivalence Evaluation for Text-to-SQL","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:39.929070Z"},"links":{"citing_paper":"/paper/2506.09359"},"observation_digest":"sha256:6654ebdd706babf63f2a7efeaa12168aa113ef28d378e03a6a11e3369910bdd1","observation_id":"ee3d974a-16e3-4e4b-ab49-de67b1410c89","resolution":{"observed_at":"2026-08-07T04:54:40.324756Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T04:54:40.311471Z","title":"Cosette: An automated prover for sql","venue":null,"work_id":"9141d2bb-bd42-4e43-8d17-e41e436b8983","year":2017},"citing_paper":{"arxiv_id":"2506.09359","last_updated":"2025-06-11T03:16:39Z","snapshot_observed_at":"2026-08-07T04:47:53.823224Z","submitted_at":"2025-06-11T03:16:39Z","title":"Taming SQL Complexity: LLM-Based Equivalence Evaluation for Text-to-SQL","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:39.934539Z"},"links":{"citing_paper":"/paper/2506.09359"},"observation_digest":"sha256:f80ae3ce3cd9fe86201edf63120980576da8007dab88488b53989a0b4b27a680","observation_id":"ce84dcb2-8de7-458b-b9cf-a6c1d822cdf8","resolution":{"observed_at":"2026-08-07T04:54:40.314871Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T04:54:40.298732Z","title":"Axiomatic foundations and algorithms for deciding semantic equivalences of sql queries","venue":null,"work_id":"c22c7fb8-0aee-492a-86d4-68c4120cef2d","year":2018},"citing_paper":{"arxiv_id":"2506.09359","last_updated":"2025-06-11T03:16:39Z","snapshot_observed_at":"2026-08-07T04:47:53.823224Z","submitted_at":"2025-06-11T03:16:39Z","title":"Taming SQL Complexity: LLM-Based Equivalence Evaluation for Text-to-SQL","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:39.938221Z"},"links":{"citing_paper":"/paper/2506.09359"},"observation_digest":"sha256:0afe0f4e07ebd702a3fa4e12dbf3510907088d362e0ffe9d8749030a6cf43787","observation_id":"194dda6a-ec43-4677-a44d-823e6a9d4433","resolution":{"observed_at":"2026-08-07T04:54:40.303591Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T04:54:40.287952Z","title":"sql-eval, n.d","venue":null,"work_id":"a9f6c7a2-ea9c-4bac-83f3-d2a630af3394","year":2024},"citing_paper":{"arxiv_id":"2506.09359","last_updated":"2025-06-11T03:16:39Z","snapshot_observed_at":"2026-08-07T04:47:53.823224Z","submitted_at":"2025-06-11T03:16:39Z","title":"Taming SQL Complexity: LLM-Based Equivalence Evaluation for Text-to-SQL","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:39.941954Z"},"links":{"citing_paper":"/paper/2506.09359"},"observation_digest":"sha256:12d024b3eac8e5bc802441e2ad6e76ea200c912b03c9ab48b69982851bc9f101","observation_id":"4b3f7c77-a394-4359-b73a-f723ce6e362b","resolution":{"observed_at":"2026-08-07T04:54:40.291736Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T04:54:40.277061Z","title":"and Singh, M","venue":null,"work_id":"16a1a37c-645d-4446-90bc-a056c9787ea4","year":2024},"citing_paper":{"arxiv_id":"2506.09359","last_updated":"2025-06-11T03:16:39Z","snapshot_observed_at":"2026-08-07T04:47:53.823224Z","submitted_at":"2025-06-11T03:16:39Z","title":"Taming SQL Complexity: LLM-Based Equivalence Evaluation for Text-to-SQL","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:39.945885Z"},"links":{"citing_paper":"/paper/2506.09359"},"observation_digest":"sha256:e6351aa2769a6b13367063e6fe904d13708670791db49025a9d5939acf72da88","observation_id":"68d08277-000e-4144-9247-94fc2c590247","resolution":{"observed_at":"2026-08-07T04:54:40.280560Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T04:54:39.949177Z","title":"Proving query equivalence using linear integer arithmetic","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.09359","last_updated":"2025-06-11T03:16:39Z","snapshot_observed_at":"2026-08-07T04:47:53.823224Z","submitted_at":"2025-06-11T03:16:39Z","title":"Taming SQL Complexity: LLM-Based Equivalence Evaluation for Text-to-SQL","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:39.949177Z"},"links":{"citing_paper":"/paper/2506.09359"},"observation_digest":"sha256:1997930e93d21c2d8f95eaefad73fb58e4563280a35a9b304fdfb02e3e71d9c6","observation_id":"043abf17-8a7e-4cb5-8f6e-d4ccf0ad1264","resolution":{"observed_at":"2026-08-07T04:54:39.949177Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.15594","last_updated":"2025-10-19T10:32:43Z","snapshot_observed_at":"2026-08-02T10:23:50.881300Z","submitted_at":"2024-11-23T16:03:35Z","title":"A Survey on LLM-as-a-Judge","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.15594","snapshot_observed_at":"2026-08-07T04:54:39.952751Z","title":"A survey on llm-as-a-judge, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.09359","last_updated":"2025-06-11T03:16:39Z","snapshot_observed_at":"2026-08-07T04:47:53.823224Z","submitted_at":"2025-06-11T03:16:39Z","title":"Taming SQL Complexity: LLM-Based Equivalence Evaluation for Text-to-SQL","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:39.952751Z"},"links":{"cited_paper":"/paper/2411.15594","citing_paper":"/paper/2506.09359"},"observation_digest":"sha256:665dde07d394f944a95967c3f2be85744b108fd24b9d871c4cd8d118d1ec6a20","observation_id":"c7ea9542-602d-41e9-8280-cb730d704646","resolution":{"observed_at":"2026-08-07T04:54:39.952751Z","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":"2026-08-07T04:54:39.956707Z","title":"FLEX : Expert-level false-less EX ecution metric for text-to- SQL benchmark","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.09359","last_updated":"2025-06-11T03:16:39Z","snapshot_observed_at":"2026-08-07T04:47:53.823224Z","submitted_at":"2025-06-11T03:16:39Z","title":"Taming SQL Complexity: LLM-Based Equivalence Evaluation for Text-to-SQL","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:39.956707Z"},"links":{"citing_paper":"/paper/2506.09359"},"observation_digest":"sha256:af23fb30029cb863b814fbb3c94f2ff7132056b65941a8d2eff2cbbbb8c104dd","observation_id":"f4db2795-a666-4a34-b082-cce020cff8bc","resolution":{"observed_at":"2026-08-07T04:54:39.956707Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.14441","last_updated":"2024-03-21T14:46:45Z","snapshot_observed_at":"2026-08-08T19:40:46.022242Z","submitted_at":"2024-03-21T14:46:45Z","title":"Quantifying Semantic Query Similarity for Automated Linear SQL Grading: A Graph-based Approach","version":1},"cited_work":{"arxiv_id":"2403.14441","doi":null,"metadata_source":"pith","pith_arxiv_id":"2403.14441","snapshot_observed_at":"2026-08-07T04:54:40.183442Z","title":"Quantifying Semantic Query Similarity for Automated Linear SQL Grading: A Graph-based Approach","venue":"cs.DB","work_id":"f84d666c-3305-4f92-ae2b-f6c8762e385f","year":2024},"citing_paper":{"arxiv_id":"2506.09359","last_updated":"2025-06-11T03:16:39Z","snapshot_observed_at":"2026-08-07T04:47:53.823224Z","submitted_at":"2025-06-11T03:16:39Z","title":"Taming SQL Complexity: LLM-Based Equivalence Evaluation for Text-to-SQL","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:39.960745Z"},"links":{"cited_paper":"/paper/2403.14441","citing_paper":"/paper/2506.09359"},"observation_digest":"sha256:e230f069eb215b097e9cb1c72ae4c8457c13f35ca51a437ea640a7fdc85bf665","observation_id":"cba47b32-f89d-4e18-b778-c27ceb3a6d6d","resolution":{"observed_at":"2026-08-07T04:54:40.187925Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T04:54:40.266299Z","title":"Can llm already serve as a database interface? a big bench for large-scale database grounded text-to-sqls","venue":null,"work_id":"3b2d2325-597a-47c8-8a9c-05ec5671d863","year":2024},"citing_paper":{"arxiv_id":"2506.09359","last_updated":"2025-06-11T03:16:39Z","snapshot_observed_at":"2026-08-07T04:47:53.823224Z","submitted_at":"2025-06-11T03:16:39Z","title":"Taming SQL Complexity: LLM-Based Equivalence Evaluation for Text-to-SQL","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:39.964879Z"},"links":{"citing_paper":"/paper/2506.09359"},"observation_digest":"sha256:e2bc624aa6d95c81e57b121c0b6efbf4465ec36a84387cbfdd702b85d100e4b5","observation_id":"dd30f3e6-e40a-4d3e-959b-08abf2442b3e","resolution":{"observed_at":"2026-08-07T04:54:40.270169Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T04:54:40.255434Z","title":"D e T riever: Decoder-representation-based retriever for improving NL 2 SQL in-context learning","venue":null,"work_id":"ad4ab1d1-76e4-48ce-8936-5d839a80cf91","year":2025},"citing_paper":{"arxiv_id":"2506.09359","last_updated":"2025-06-11T03:16:39Z","snapshot_observed_at":"2026-08-07T04:47:53.823224Z","submitted_at":"2025-06-11T03:16:39Z","title":"Taming SQL Complexity: LLM-Based Equivalence Evaluation for Text-to-SQL","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:39.968919Z"},"links":{"citing_paper":"/paper/2506.09359"},"observation_digest":"sha256:09d3a7872c7a804ac45ebd8b299ed3d9364cdcfaafbedae1a14e45a42037abab","observation_id":"e8329e75-bafa-4e88-9e72-69b8b94a23fe","resolution":{"observed_at":"2026-08-07T04:54:40.259191Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T04:54:40.243793Z","title":"Calibrating LLM -based evaluator","venue":null,"work_id":"51f1f547-ce15-4ccd-b197-b5585b0c7752","year":2024},"citing_paper":{"arxiv_id":"2506.09359","last_updated":"2025-06-11T03:16:39Z","snapshot_observed_at":"2026-08-07T04:47:53.823224Z","submitted_at":"2025-06-11T03:16:39Z","title":"Taming SQL Complexity: LLM-Based Equivalence Evaluation for Text-to-SQL","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:39.972530Z"},"links":{"citing_paper":"/paper/2506.09359"},"observation_digest":"sha256:5a84de8ed9287430a975b338ccf13598edbab5538cb5f75eb3208bfa23d8d9ab","observation_id":"eded44f0-435b-4288-89f8-c71023f8ea13","resolution":{"observed_at":"2026-08-07T04:54:40.248458Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T04:54:39.976342Z","title":"HD -eval: Aligning large language model evaluators through hierarchical criteria decomposition","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09359","last_updated":"2025-06-11T03:16:39Z","snapshot_observed_at":"2026-08-07T04:47:53.823224Z","submitted_at":"2025-06-11T03:16:39Z","title":"Taming SQL Complexity: LLM-Based Equivalence Evaluation for Text-to-SQL","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:39.976342Z"},"links":{"citing_paper":"/paper/2506.09359"},"observation_digest":"sha256:ee5e8b2558a01d9ca2201143529af747942eb6690b9afc79971aeb16c593f4fe","observation_id":"39b4f32d-3f9a-47d4-8915-dbf7180d9172","resolution":{"observed_at":"2026-08-07T04:54:39.976342Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2008.04759","last_updated":"2020-08-11T15:01:52Z","snapshot_observed_at":"2026-08-04T00:22:44.366896Z","submitted_at":"2020-08-11T15:01:52Z","title":"Hybrid Ranking Network for Text-to-SQL","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2008.04759","snapshot_observed_at":"2026-08-07T04:54:39.979903Z","title":"Hybrid ranking network for text-to-sql, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.09359","last_updated":"2025-06-11T03:16:39Z","snapshot_observed_at":"2026-08-07T04:47:53.823224Z","submitted_at":"2025-06-11T03:16:39Z","title":"Taming SQL Complexity: LLM-Based Equivalence Evaluation for Text-to-SQL","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:39.979903Z"},"links":{"cited_paper":"/paper/2008.04759","citing_paper":"/paper/2506.09359"},"observation_digest":"sha256:68e74854dda9fd042c0c4f86f08578e4df321f73a289b9b119ab33f6e712fc5b","observation_id":"345bc2ae-3237-48c6-b354-dd9ca58d03b2","resolution":{"observed_at":"2026-08-07T04:54:39.979903Z","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":"2026-08-07T04:54:40.233245Z","title":"and Rafiei, D","venue":null,"work_id":"f7666ab4-9476-47aa-b3c0-801ed95b037c","year":2024},"citing_paper":{"arxiv_id":"2506.09359","last_updated":"2025-06-11T03:16:39Z","snapshot_observed_at":"2026-08-07T04:47:53.823224Z","submitted_at":"2025-06-11T03:16:39Z","title":"Taming SQL Complexity: LLM-Based Equivalence Evaluation for Text-to-SQL","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:39.983899Z"},"links":{"citing_paper":"/paper/2506.09359"},"observation_digest":"sha256:19661225bd5e8a28b9ff67188522260f43d60890c78d868de45933c5b8d18055","observation_id":"134a1b63-c701-4fd2-b269-8c49c31172eb","resolution":{"observed_at":"2026-08-07T04:54:40.236833Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T04:54:39.987404Z","title":"and Rafiei, D","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09359","last_updated":"2025-06-11T03:16:39Z","snapshot_observed_at":"2026-08-07T04:47:53.823224Z","submitted_at":"2025-06-11T03:16:39Z","title":"Taming SQL Complexity: LLM-Based Equivalence Evaluation for Text-to-SQL","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:39.987404Z"},"links":{"citing_paper":"/paper/2506.09359"},"observation_digest":"sha256:d795e2035aa567c2c2f69ea79af12457150bec788bd08abb7de8f9f77f66206e","observation_id":"8b61ea1a-7a1d-4705-8116-eeb623a27766","resolution":{"observed_at":"2026-08-07T04:54:39.987404Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.01943","last_updated":"2024-10-02T18:41:35Z","snapshot_observed_at":"2026-07-06T19:26:33.330434Z","submitted_at":"2024-10-02T18:41:35Z","title":"CHASE-SQL: Multi-Path Reasoning and Preference Optimized Candidate Selection in Text-to-SQL","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.01943","snapshot_observed_at":"2026-08-07T04:54:39.995309Z","title":"T., Gan, Y., Saberi, A., Ozcan, F., and Arik, S","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09359","last_updated":"2025-06-11T03:16:39Z","snapshot_observed_at":"2026-08-07T04:47:53.823224Z","submitted_at":"2025-06-11T03:16:39Z","title":"Taming SQL Complexity: LLM-Based Equivalence Evaluation for Text-to-SQL","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:39.995309Z"},"links":{"cited_paper":"/paper/2410.01943","citing_paper":"/paper/2506.09359"},"observation_digest":"sha256:09ce8f5e4156bc8545da896144edeb5ebcd4141b54bda0f17018a9bc2a4b2b19","observation_id":"7fb415af-a983-4a56-bb29-03c8c70eeaf9","resolution":{"observed_at":"2026-08-07T04:54:39.995309Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.16204","last_updated":"2024-03-24T15:57:24Z","snapshot_observed_at":"2026-08-09T11:10:25.581983Z","submitted_at":"2024-03-24T15:57:24Z","title":"SQL-Encoder: Improving NL2SQL In-Context Learning Through a Context-Aware Encoder","version":1},"cited_work":{"arxiv_id":"2403.16204","doi":null,"metadata_source":"pith","pith_arxiv_id":"2403.16204","snapshot_observed_at":"2026-08-07T04:54:40.142264Z","title":"SQL-Encoder: Improving NL2SQL In-Context Learning Through a Context-Aware Encoder","venue":"cs.CL","work_id":"48d391a8-6e64-48ad-9a25-ad676d37d70c","year":2024},"citing_paper":{"arxiv_id":"2506.09359","last_updated":"2025-06-11T03:16:39Z","snapshot_observed_at":"2026-08-07T04:47:53.823224Z","submitted_at":"2025-06-11T03:16:39Z","title":"Taming SQL Complexity: LLM-Based Equivalence Evaluation for Text-to-SQL","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:39.998840Z"},"links":{"cited_paper":"/paper/2403.16204","citing_paper":"/paper/2506.09359"},"observation_digest":"sha256:e6973932da5c7a0a4b75ac24501c7a489ebbc818d5c368455826d2d36ea568c0","observation_id":"960f1f04-9550-46c2-b814-854327a4f518","resolution":{"observed_at":"2026-08-07T04:54:40.148099Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.12733","last_updated":"2024-10-02T18:19:15Z","snapshot_observed_at":"2026-08-03T14:39:50.118256Z","submitted_at":"2024-08-22T20:50:48Z","title":"SQL-GEN: Bridging the Dialect Gap for Text-to-SQL Via Synthetic Data And Model Merging","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.12733","snapshot_observed_at":"2026-08-07T04:54:40.002669Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09359","last_updated":"2025-06-11T03:16:39Z","snapshot_observed_at":"2026-08-07T04:47:53.823224Z","submitted_at":"2025-06-11T03:16:39Z","title":"Taming SQL Complexity: LLM-Based Equivalence Evaluation for Text-to-SQL","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:40.002669Z"},"links":{"cited_paper":"/paper/2408.12733","citing_paper":"/paper/2506.09359"},"observation_digest":"sha256:6b805a7fa8aa897b52a1a5989ef8ab734ee5a24cc03fb82323c887fa6744773a","observation_id":"21ec9455-4851-44a9-a821-3ee198ddea3d","resolution":{"observed_at":"2026-08-07T04:54:40.002669Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.16755","last_updated":"2024-11-25T19:43:07Z","snapshot_observed_at":"2026-08-02T16:46:24.597803Z","submitted_at":"2024-05-27T01:54:16Z","title":"CHESS: Contextual Harnessing for Efficient SQL Synthesis","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.16755","snapshot_observed_at":"2026-08-07T04:54:40.006571Z","title":"Chess: Contextual harnessing for efficient sql synthesis, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09359","last_updated":"2025-06-11T03:16:39Z","snapshot_observed_at":"2026-08-07T04:47:53.823224Z","submitted_at":"2025-06-11T03:16:39Z","title":"Taming SQL Complexity: LLM-Based Equivalence Evaluation for Text-to-SQL","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:40.006571Z"},"links":{"cited_paper":"/paper/2405.16755","citing_paper":"/paper/2506.09359"},"observation_digest":"sha256:e7abdfa50b77e4d8b527b5ada8fe26666577e5606c0beeed0ca6d344270ac563","observation_id":"a0c336f1-a693-4b94-a69d-085e950a02e6","resolution":{"observed_at":"2026-08-07T04:54:40.006571Z","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":"2026-08-07T04:54:40.010704Z","title":"Is C hat GPT a good NLG evaluator? a preliminary study","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.09359","last_updated":"2025-06-11T03:16:39Z","snapshot_observed_at":"2026-08-07T04:47:53.823224Z","submitted_at":"2025-06-11T03:16:39Z","title":"Taming SQL Complexity: LLM-Based Equivalence Evaluation for Text-to-SQL","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:40.010704Z"},"links":{"citing_paper":"/paper/2506.09359"},"observation_digest":"sha256:c121d6f2eda27cce7b8d5c3d0e3ac0f133420b2e6facf21d2659c99ced9d39b5","observation_id":"0a0a4edc-8a85-4047-83bf-ee7cbb794297","resolution":{"observed_at":"2026-08-07T04:54:40.010704Z","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":"2026-08-07T04:54:40.014488Z","title":"S pider: A large-scale human-labeled dataset for complex and cross-domain semantic parsing and text-to- SQL task","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.09359","last_updated":"2025-06-11T03:16:39Z","snapshot_observed_at":"2026-08-07T04:47:53.823224Z","submitted_at":"2025-06-11T03:16:39Z","title":"Taming SQL Complexity: LLM-Based Equivalence Evaluation for Text-to-SQL","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:40.014488Z"},"links":{"citing_paper":"/paper/2506.09359"},"observation_digest":"sha256:a8041b99f8b298ba5b2fd99eeed3c461680a35c4927b812437fc4ec29a4303a3","observation_id":"1aef7a10-5fdb-4f44-b039-78b1058e7add","resolution":{"observed_at":"2026-08-07T04:54:40.014488Z","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":"2026-08-07T04:54:40.215930Z","title":"Towards database-free text-to- SQL evaluation: A graph-based metric for functional correctness","venue":null,"work_id":"fd68b029-ba97-4778-9850-e61ef2e19ec0","year":2025},"citing_paper":{"arxiv_id":"2506.09359","last_updated":"2025-06-11T03:16:39Z","snapshot_observed_at":"2026-08-07T04:47:53.823224Z","submitted_at":"2025-06-11T03:16:39Z","title":"Taming SQL Complexity: LLM-Based Equivalence Evaluation for Text-to-SQL","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:40.018386Z"},"links":{"citing_paper":"/paper/2506.09359"},"observation_digest":"sha256:64e4e45f201084dde23efbd9617fb52565b9442611d70e0b77a0f8b36435f93e","observation_id":"d1c3dc02-7122-4509-94bd-0140edfbf745","resolution":{"observed_at":"2026-08-07T04:54:40.219860Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.06326","last_updated":"2025-05-16T05:30:57Z","snapshot_observed_at":"2026-07-06T18:28:12.010251Z","submitted_at":"2024-06-10T14:42:20Z","title":"Self-Tuning: Instructing LLMs to Effectively Acquire New Knowledge through Self-Teaching","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.06326","snapshot_observed_at":"2026-08-07T04:54:40.022291Z","title":"Self-tuning: Instructing llms to effectively acquire new knowledge through self-teaching, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09359","last_updated":"2025-06-11T03:16:39Z","snapshot_observed_at":"2026-08-07T04:47:53.823224Z","submitted_at":"2025-06-11T03:16:39Z","title":"Taming SQL Complexity: LLM-Based Equivalence Evaluation for Text-to-SQL","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:40.022291Z"},"links":{"cited_paper":"/paper/2406.06326","citing_paper":"/paper/2506.09359"},"observation_digest":"sha256:bb1511b8130f9034f8b09fdb0eea2136af61d08d61989c3f3ed4dd99b85c50c0","observation_id":"ae84871f-28a7-4f6c-83ee-b2c15c4961d2","resolution":{"observed_at":"2026-08-07T04:54:40.022291Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.10321","last_updated":"2025-03-12T03:16:27Z","snapshot_observed_at":"2026-08-05T05:22:50.304746Z","submitted_at":"2023-12-16T05:01:23Z","title":"LLM-SQL-Solver: Can LLMs Determine SQL Equivalence?","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.10321","snapshot_observed_at":"2026-08-07T04:54:40.025942Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09359","last_updated":"2025-06-11T03:16:39Z","snapshot_observed_at":"2026-08-07T04:47:53.823224Z","submitted_at":"2025-06-11T03:16:39Z","title":"Taming SQL Complexity: LLM-Based Equivalence Evaluation for Text-to-SQL","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-07T04:54:40.025942Z"},"links":{"cited_paper":"/paper/2312.10321","citing_paper":"/paper/2506.09359"},"observation_digest":"sha256:d3b13707c0eda40717552dbbaa2061fb628620b12d86bbde8dc99a7c5a723d08","observation_id":"672a3ee4-9f4f-4db3-851c-dd44a0700192","resolution":{"observed_at":"2026-08-07T04:54:40.025942Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2506.09359","last_updated":"2025-06-11T03:16:39Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-07T04:47:53.823224Z","submitted_at":"2025-06-11T03:16:39Z","title":"Taming SQL Complexity: LLM-Based Equivalence Evaluation for Text-to-SQL"},"reference_resolution":{"displayed":28,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":15,"verified_exact":2,"verified_fuzzy":11},"total_outbound_references":28},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2506.09359."}