{"as_of":"2026-08-08T06:15:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:beef3827c2714961b7432246a3784ae26cc34d92778a670c1ab7d6dfc92656c9","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":7,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":7,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":7,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":7,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T14:26:57.581628Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-10T06:15:00.866473Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2407.15186","last_updated":"2025-06-03T14:40:01Z","snapshot_observed_at":"2026-08-08T00:42:14.053796Z","submitted_at":"2024-07-21T14:48:23Z","title":"A Survey on Employing Large Language Models for Text-to-SQL Tasks","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.15186","snapshot_observed_at":"2026-08-07T14:26:57.581628Z","title":"A survey on employing large language models for text-to-sql tasks,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.18929","last_updated":"2025-05-25T01:45:00Z","snapshot_observed_at":"2026-08-07T14:20:58.554541Z","submitted_at":"2025-05-25T01:45:00Z","title":"Meta-aware Learning in text-to-SQL Large Language Model","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T14:26:57.581628Z"},"links":{"cited_paper":"/paper/2407.15186","citing_paper":"/paper/2505.18929"},"observation_digest":"sha256:5d370b3cbdfbb5dcfacb97698c2e5eea2f5c3ad1c9570957cfb33fb4a305795e","observation_id":"cb631ec2-e0ca-41c6-8f93-642c7f1c21cc","resolution":{"observed_at":"2026-08-07T14:26:57.581628Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.15186","last_updated":"2025-06-03T14:40:01Z","snapshot_observed_at":"2026-08-08T00:42:14.053796Z","submitted_at":"2024-07-21T14:48:23Z","title":"A Survey on Employing Large Language Models for Text-to-SQL Tasks","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.15186","snapshot_observed_at":"2026-08-07T05:38:16.278842Z","title":"A survey on employing large language models for text-to-sql tasks,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07423","last_updated":"2025-06-09T04:44:31Z","snapshot_observed_at":"2026-08-07T05:32:01.319636Z","submitted_at":"2025-06-09T04:44:31Z","title":"SEED: Enhancing Text-to-SQL Performance and Practical Usability Through Automatic Evidence Generation","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T05:38:16.278842Z"},"links":{"cited_paper":"/paper/2407.15186","citing_paper":"/paper/2506.07423"},"observation_digest":"sha256:3984f83d4666cbdf5adeb5a479c7d7f6185b97eba084aff5e7560a7e0a8e7e65","observation_id":"5fd2ee94-8e8d-40df-ae95-99809a23204d","resolution":{"observed_at":"2026-08-07T05:38:16.278842Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.15186","last_updated":"2025-06-03T14:40:01Z","snapshot_observed_at":"2026-08-08T00:42:14.053796Z","submitted_at":"2024-07-21T14:48:23Z","title":"A Survey on Employing Large Language Models for Text-to-SQL Tasks","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.15186","snapshot_observed_at":"2026-08-07T00:41:26.016771Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.13188","last_updated":"2025-06-16T07:55:44Z","snapshot_observed_at":"2026-08-07T00:34:23.435428Z","submitted_at":"2025-06-16T07:55:44Z","title":"SPOT: Bridging Natural Language and Geospatial Search for Investigative Journalists","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-07T00:41:26.016771Z"},"links":{"cited_paper":"/paper/2407.15186","citing_paper":"/paper/2506.13188"},"observation_digest":"sha256:da98c96b635b39010147f524c7e57845b16c8fb25a6f1e33f5d0789429a9c265","observation_id":"423e2eae-dbff-462e-856b-f3144e41386e","resolution":{"observed_at":"2026-08-07T00:41:26.016771Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.15186","last_updated":"2025-06-03T14:40:01Z","snapshot_observed_at":"2026-08-08T00:42:14.053796Z","submitted_at":"2024-07-21T14:48:23Z","title":"A Survey on Employing Large Language Models for Text-to-SQL Tasks","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.15186","snapshot_observed_at":"2026-08-05T15:31:15.286631Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.19807","last_updated":"2025-08-27T11:50:42Z","snapshot_observed_at":"2026-08-05T15:31:14.634045Z","submitted_at":"2025-08-27T11:50:42Z","title":"Bootstrapping Learned Cost Models with Synthetic SQL Queries","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-05T15:31:15.286631Z"},"links":{"cited_paper":"/paper/2407.15186","citing_paper":"/paper/2508.19807"},"observation_digest":"sha256:36980522c66abfba76a0147ec4b566854a7bb472990b73690df641b77b66f4b0","observation_id":"11eda916-c3fd-4949-99bd-430b8a13c936","resolution":{"observed_at":"2026-08-05T15:31:15.286631Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.15186","last_updated":"2025-06-03T14:40:01Z","snapshot_observed_at":"2026-08-08T00:42:14.053796Z","submitted_at":"2024-07-21T14:48:23Z","title":"A Survey on Employing Large Language Models for Text-to-SQL Tasks","version":5},"cited_work":{"arxiv_id":"2407.15186","doi":"10.48550/arxiv.2407.15186","metadata_source":"arxiv_reference","pith_arxiv_id":"2407.15186","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"arXiv preprint arXiv:2407.15186 , year=","venue":null,"work_id":"55257a66-a8c4-4d90-b265-362585eedec3","year":2024},"citing_paper":{"arxiv_id":"2605.04065","last_updated":"2026-05-07T04:49:30Z","snapshot_observed_at":"2026-07-06T23:16:54.673178Z","submitted_at":"2026-04-11T07:26:04Z","title":"Free Energy-Driven Reinforcement Learning with Adaptive Advantage Shaping for Unsupervised Reasoning in LLMs","version":2},"reference_index":192,"source":"arxiv_source","source_observed_at":"2026-05-10T16:58:10.013475Z"},"links":{"cited_paper":"/paper/2407.15186","citing_paper":"/paper/2605.04065"},"observation_digest":"sha256:c58829329045e64f0a12497dbf8daafd70c32e167761ec97dca2c0d10a86f856","observation_id":"bb44deb7-f1ee-427e-a3c2-ab04e345c6a7","resolution":{"observed_at":"2026-05-11T07:45:59.628421Z","resolver_source":"arxiv_id","status":"verified_exact"},"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":"2407.15186","last_updated":"2025-06-03T14:40:01Z","snapshot_observed_at":"2026-08-08T00:42:14.053796Z","submitted_at":"2024-07-21T14:48:23Z","title":"A Survey on Employing Large Language Models for Text-to-SQL Tasks","version":5},"cited_work":{"arxiv_id":"2407.15186","doi":"10.48550/arxiv.2407.15186","metadata_source":"arxiv_reference","pith_arxiv_id":"2407.15186","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"arXiv preprint arXiv:2407.15186 , year=","venue":null,"work_id":"55257a66-a8c4-4d90-b265-362585eedec3","year":2024},"citing_paper":{"arxiv_id":"2605.04066","last_updated":"2026-05-07T04:57:40Z","snapshot_observed_at":"2026-08-02T15:49:26.057284Z","submitted_at":"2026-04-11T07:34:59Z","title":"Adapt to Thrive! Adaptive Power-Mean Policy Optimization for Improved LLM Reasoning","version":2},"reference_index":177,"source":"arxiv_source","source_observed_at":"2026-05-10T16:51:19.555272Z"},"links":{"cited_paper":"/paper/2407.15186","citing_paper":"/paper/2605.04066"},"observation_digest":"sha256:07a002d93d6d695d8f0ab23cb6a611255005b76cc74e1427478148016c6e92ae","observation_id":"c2916849-c90a-42e5-bbb4-43851a1ac54e","resolution":{"observed_at":"2026-05-11T08:01:00.315037Z","resolver_source":"arxiv_id","status":"verified_exact"},"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":"2407.15186","last_updated":"2025-06-03T14:40:01Z","snapshot_observed_at":"2026-08-08T00:42:14.053796Z","submitted_at":"2024-07-21T14:48:23Z","title":"A Survey on Employing Large Language Models for Text-to-SQL Tasks","version":5},"cited_work":{"arxiv_id":"2407.15186","doi":"10.48550/arxiv.2407.15186","metadata_source":"arxiv_reference","pith_arxiv_id":"2407.15186","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"arXiv preprint arXiv:2407.15186 , year=","venue":null,"work_id":"55257a66-a8c4-4d90-b265-362585eedec3","year":2024},"citing_paper":{"arxiv_id":"2606.17094","last_updated":"2026-06-13T15:47:53Z","snapshot_observed_at":"2026-07-06T23:52:42.390632Z","submitted_at":"2026-06-13T15:47:53Z","title":"LogCopilot: Automating Log Aggregation Analysis through Large Language Models","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-06-27T04:19:22.844388Z"},"links":{"cited_paper":"/paper/2407.15186","citing_paper":"/paper/2606.17094"},"observation_digest":"sha256:0fcb071e2e98e63b94fc2e828a1636a8f5209c5b068052243f163f3b0ec918c2","observation_id":"02f7889e-50f4-4fe4-9b08-7230a6dcb506","resolution":{"observed_at":"2026-06-27T04:20:31.790017Z","resolver_source":"arxiv_id","status":"verified_exact"},"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"}}],"links":{"evidence":"/evidence","html":"/paper/2407.15186/citation-record","integrity":"/paper/2407.15186/integrity","json":"/paper/2407.15186/citation-record.json","paper":"/paper/2407.15186"},"outbound":[],"paper":{"arxiv_id":"2407.15186","last_updated":"2025-06-03T14:40:01Z","latest_version":5,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-08T00:42:14.053796Z","submitted_at":"2024-07-21T14:48:23Z","title":"A Survey on Employing Large Language Models for Text-to-SQL Tasks"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2407.15186."}