{"as_of":"2026-08-07T22:11:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:de5820551a7f19c3128f30a0f80494340a0cd50290ec85487c01066ff75f2371","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":5,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":5,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":5,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":5,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T14:36:12.537427Z","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":"2026-05-11T08:00:59.965558Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2312.03463","last_updated":"2025-02-22T08:32:05Z","snapshot_observed_at":"2026-07-06T16:57:42.671972Z","submitted_at":"2023-12-06T12:37:28Z","title":"DBCopilot: Natural Language Querying over Massive Databases via Schema Routing","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.03463","snapshot_observed_at":"2026-08-07T14:36:12.537427Z","title":"Preprint, arXiv:2312.03463","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.18363","last_updated":"2025-05-23T20:42:36Z","snapshot_observed_at":"2026-08-07T14:30:25.653265Z","submitted_at":"2025-05-23T20:42:36Z","title":"SchemaGraphSQL: Efficient Schema Linking with Pathfinding Graph Algorithms for Text-to-SQL on Large-Scale Databases","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T14:36:12.537427Z"},"links":{"cited_paper":"/paper/2312.03463","citing_paper":"/paper/2505.18363"},"observation_digest":"sha256:63a04f77784aa3caaa74945cd4a0289dac4a8fe720404fb3fd47c7bef0a4b3c7","observation_id":"a0f2a34b-a9e9-4849-9e87-e16a90c81359","resolution":{"observed_at":"2026-08-07T14:36:12.537427Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.03463","last_updated":"2025-02-22T08:32:05Z","snapshot_observed_at":"2026-07-06T16:57:42.671972Z","submitted_at":"2023-12-06T12:37:28Z","title":"DBCopilot: Natural Language Querying over Massive Databases via Schema Routing","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.03463","snapshot_observed_at":"2026-08-07T13:12:44.687279Z","title":"Dbcopilot: Scaling natural language querying to massive databases","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.23838","last_updated":"2025-05-28T13:23:38Z","snapshot_observed_at":"2026-08-07T13:07:18.579375Z","submitted_at":"2025-05-28T13:23:38Z","title":"Exploring the Landscape of Text-to-SQL with Large Language Models: Progresses, Challenges and Opportunities","version":1},"reference_index":129,"source":"pdf_text","source_observed_at":"2026-08-07T13:12:44.687279Z"},"links":{"cited_paper":"/paper/2312.03463","citing_paper":"/paper/2505.23838"},"observation_digest":"sha256:556417a90e5adb3cfaa3f37257646a8dc3ad201d53661a951c403e63ba5c09f4","observation_id":"ce385d86-c3f7-4fc6-a5a5-efd067ca29e6","resolution":{"observed_at":"2026-08-07T13:12:44.687279Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.03463","last_updated":"2025-02-22T08:32:05Z","snapshot_observed_at":"2026-07-06T16:57:42.671972Z","submitted_at":"2023-12-06T12:37:28Z","title":"DBCopilot: Natural Language Querying over Massive Databases via Schema Routing","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.03463","snapshot_observed_at":"2026-08-06T11:09:18.903040Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.23104","last_updated":"2025-07-30T21:09:47Z","snapshot_observed_at":"2026-08-06T11:09:15.906603Z","submitted_at":"2025-07-30T21:09:47Z","title":"RASL: Retrieval Augmented Schema Linking for Massive Database Text-to-SQL","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T11:09:18.903040Z"},"links":{"cited_paper":"/paper/2312.03463","citing_paper":"/paper/2507.23104"},"observation_digest":"sha256:76d8c0686cb801d5f913078981557fd1c112e246624da87e324b0445e74a3e48","observation_id":"06935143-9fc6-4cec-8256-427dc98c871e","resolution":{"observed_at":"2026-08-06T11:09:18.903040Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.03463","last_updated":"2025-02-22T08:32:05Z","snapshot_observed_at":"2026-07-06T16:57:42.671972Z","submitted_at":"2023-12-06T12:37:28Z","title":"DBCopilot: Natural Language Querying over Massive Databases via Schema Routing","version":3},"cited_work":{"arxiv_id":"2312.03463","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2312.03463","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2312.03463 , year=","venue":null,"work_id":"bc32467d-b106-4c15-9c20-1aa9e75c12ed","year":null},"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":184,"source":"arxiv_source","source_observed_at":"2026-05-10T16:58:10.013475Z"},"links":{"cited_paper":"/paper/2312.03463","citing_paper":"/paper/2605.04065"},"observation_digest":"sha256:61ce3cce315bd2d3bac36a8eab4687bba24e38d61941408a7f83b81def9ccb2a","observation_id":"6f089b0f-3f81-4bc2-b160-78a8c359bd8e","resolution":{"observed_at":"2026-05-11T07:45:59.822109Z","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":"2312.03463","last_updated":"2025-02-22T08:32:05Z","snapshot_observed_at":"2026-07-06T16:57:42.671972Z","submitted_at":"2023-12-06T12:37:28Z","title":"DBCopilot: Natural Language Querying over Massive Databases via Schema Routing","version":3},"cited_work":{"arxiv_id":"2312.03463","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2312.03463","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2312.03463 , year=","venue":null,"work_id":"bc32467d-b106-4c15-9c20-1aa9e75c12ed","year":null},"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":169,"source":"arxiv_source","source_observed_at":"2026-05-10T16:51:19.555272Z"},"links":{"cited_paper":"/paper/2312.03463","citing_paper":"/paper/2605.04066"},"observation_digest":"sha256:63da4b64391086584e778df38714349cea671d395ff1fda567f5dfc7c87f54eb","observation_id":"9b1b4687-2310-4cce-bb53-295246db7c21","resolution":{"observed_at":"2026-05-11T08:00:59.970142Z","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/2312.03463/citation-record","integrity":"/paper/2312.03463/integrity","json":"/paper/2312.03463/citation-record.json","paper":"/paper/2312.03463"},"outbound":[],"paper":{"arxiv_id":"2312.03463","last_updated":"2025-02-22T08:32:05Z","latest_version":3,"primary_category":"cs.CL","snapshot_observed_at":"2026-07-06T16:57:42.671972Z","submitted_at":"2023-12-06T12:37:28Z","title":"DBCopilot: Natural Language Querying over Massive Databases via Schema Routing"},"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 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2312.03463."}