{"as_of":"2026-08-15T20:44:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:554fa5ecce6081216e9a0035a2c3ef9d2b335e4ecd054c23812ebd823e40a4c3","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":9,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":9,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+00:00","state":"measured"},{"denominator":9,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":9,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T18:01:47.320448Z","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":"2026-07-03T20:18:55.668544Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2406.14541","last_updated":"2025-03-13T21:19:46Z","snapshot_observed_at":"2026-08-14T08:50:29.223702Z","submitted_at":"2024-06-20T17:52:29Z","title":"Why LLMs Are Bad at Synthetic Table Generation (and what to do about it)","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.14541","snapshot_observed_at":"2026-08-11T20:53:46.135512Z","title":"Are LLMs Naturally Good at Synthetic Tabular Data Generation?","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.05153","last_updated":"2025-06-24T13:24:58Z","snapshot_observed_at":"2026-08-13T23:30:56.425366Z","submitted_at":"2024-12-06T16:10:40Z","title":"A text-to-tabular approach to generate synthetic patient data using LLMs","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-11T20:53:46.135512Z"},"links":{"cited_paper":"/paper/2406.14541","citing_paper":"/paper/2412.05153"},"observation_digest":"sha256:069fe5ca39d8b1a7886633f599b8c7443af090f0f13039a668407b1495c14525","observation_id":"913bef65-6884-4e51-abe4-b7c8ed490a9f","resolution":{"observed_at":"2026-08-11T20:53:46.135512Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.14541","last_updated":"2025-03-13T21:19:46Z","snapshot_observed_at":"2026-08-14T08:50:29.223702Z","submitted_at":"2024-06-20T17:52:29Z","title":"Why LLMs Are Bad at Synthetic Table Generation (and what to do about it)","version":3},"cited_work":{"arxiv_id":"2406.14541","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2406.14541","snapshot_observed_at":"2026-07-03T20:18:55.668544Z","title":"Are llms naturally good at synthetic tabular data generation?arXiv preprint arXiv:2406.14541, 2024d","venue":null,"work_id":"a61938e5-e781-423b-b1c6-5ddab6cd28f3","year":2024},"citing_paper":{"arxiv_id":"2501.01793","last_updated":"2025-01-03T12:52:51Z","snapshot_observed_at":"2026-08-15T07:53:47.637176Z","submitted_at":"2025-01-03T12:52:51Z","title":"Creating Artificial Students that Never Existed: Leveraging Large Language Models and CTGANs for Synthetic Data Generation","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-05-23T06:04:33.506895Z"},"links":{"cited_paper":"/paper/2406.14541","citing_paper":"/paper/2501.01793"},"observation_digest":"sha256:dc2cfd0e4205df6dbe8f4ff5c73fa98c97a5eea8198f41e4a60b5daac4de023f","observation_id":"00d6fd29-2100-4a25-9c85-c1a8ea0b6ace","resolution":{"observed_at":"2026-05-23T06:05:28.029583Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.14541","last_updated":"2025-03-13T21:19:46Z","snapshot_observed_at":"2026-08-14T08:50:29.223702Z","submitted_at":"2024-06-20T17:52:29Z","title":"Why LLMs Are Bad at Synthetic Table Generation (and what to do about it)","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.14541","snapshot_observed_at":"2026-08-10T13:53:52.299773Z","title":"B., Muralidhar, N., and Ramakrishnan, N","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.15718","last_updated":"2025-01-27T10:04:10Z","snapshot_observed_at":"2026-08-12T16:00:31.169262Z","submitted_at":"2025-01-27T10:04:10Z","title":"Making Sense of Data in the Wild: Data Analysis Automation at Scale","version":1},"reference_index":272,"source":"pdf_text","source_observed_at":"2026-08-10T13:53:52.299773Z"},"links":{"cited_paper":"/paper/2406.14541","citing_paper":"/paper/2502.15718"},"observation_digest":"sha256:3b550fe26ecc88f14f76cff0279cbcecd7d22c05720dd02df2fcd15e9f614f0c","observation_id":"e872ac54-9f5a-4eb2-9993-d157eb4bb346","resolution":{"observed_at":"2026-08-10T13:53:52.299773Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.14541","last_updated":"2025-03-13T21:19:46Z","snapshot_observed_at":"2026-08-14T08:50:29.223702Z","submitted_at":"2024-06-20T17:52:29Z","title":"Why LLMs Are Bad at Synthetic Table Generation (and what to do about it)","version":3},"cited_work":{"arxiv_id":"2406.14541","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2406.14541","snapshot_observed_at":"2026-07-03T20:18:55.668544Z","title":"Are llms naturally good at synthetic tabular data generation?arXiv preprint arXiv:2406.14541, 2024d","venue":null,"work_id":"a61938e5-e781-423b-b1c6-5ddab6cd28f3","year":2024},"citing_paper":{"arxiv_id":"2503.02161","last_updated":"2026-05-17T15:49:06Z","snapshot_observed_at":"2026-08-02T17:38:14.067857Z","submitted_at":"2025-03-04T00:47:52Z","title":"LLM-TabLogic: Preserving Inter-Column Logical Relationships in Synthetic Tabular Data via Prompt-Guided Latent Diffusion","version":3},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-23T01:05:38.969311Z"},"links":{"cited_paper":"/paper/2406.14541","citing_paper":"/paper/2503.02161"},"observation_digest":"sha256:0a998282b43f6c7318a60838c0c2851f41f6d68a40903ff08f9f9befa7c5a31d","observation_id":"b191a34b-e9af-40b1-b0e4-21a0feb6fa85","resolution":{"observed_at":"2026-05-23T01:07:19.849460Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.14541","last_updated":"2025-03-13T21:19:46Z","snapshot_observed_at":"2026-08-14T08:50:29.223702Z","submitted_at":"2024-06-20T17:52:29Z","title":"Why LLMs Are Bad at Synthetic Table Generation (and what to do about it)","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.14541","snapshot_observed_at":"2026-08-07T14:34:11.843576Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.18485","last_updated":"2025-05-24T03:19:36Z","snapshot_observed_at":"2026-08-14T14:41:43.527231Z","submitted_at":"2025-05-24T03:19:36Z","title":"The Prompt is Mightier than the Example","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T14:34:11.843576Z"},"links":{"cited_paper":"/paper/2406.14541","citing_paper":"/paper/2505.18485"},"observation_digest":"sha256:ef758db7b5682f21b4f2637969ef6245fba0ca1d8ba269a6384d4fc78e8b62ea","observation_id":"ef010d32-f54d-48f5-b3e0-d4c63da37a63","resolution":{"observed_at":"2026-08-07T14:34:11.843576Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.14541","last_updated":"2025-03-13T21:19:46Z","snapshot_observed_at":"2026-08-14T08:50:29.223702Z","submitted_at":"2024-06-20T17:52:29Z","title":"Why LLMs Are Bad at Synthetic Table Generation (and what to do about it)","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.14541","snapshot_observed_at":"2026-08-15T18:01:47.320448Z","title":"Xu, C.-T","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.19211","last_updated":"2025-07-25T12:29:58Z","snapshot_observed_at":"2026-08-15T17:55:41.992658Z","submitted_at":"2025-07-25T12:29:58Z","title":"Dependency-aware synthetic tabular data generation","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-15T18:01:47.320448Z"},"links":{"cited_paper":"/paper/2406.14541","citing_paper":"/paper/2507.19211"},"observation_digest":"sha256:7ca1d090f0d1c2d25d5c093dab62394e54c489271aaab7c0493731309dec8483","observation_id":"32280136-23ac-46df-a1b8-4f9af8638021","resolution":{"observed_at":"2026-08-15T18:01:47.320448Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.14541","last_updated":"2025-03-13T21:19:46Z","snapshot_observed_at":"2026-08-14T08:50:29.223702Z","submitted_at":"2024-06-20T17:52:29Z","title":"Why LLMs Are Bad at Synthetic Table Generation (and what to do about it)","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.14541","snapshot_observed_at":"2026-08-03T08:15:35.523537Z","title":"Why llms are bad at synthetic table generation (and what to do about it), 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.17717","last_updated":"2026-06-09T20:25:14Z","snapshot_observed_at":"2026-08-08T23:34:38.789355Z","submitted_at":"2026-01-25T06:40:25Z","title":"A Survey on Evaluating Quality and Trustworthiness in LLM-Generated Data","version":3},"reference_index":244,"source":"arxiv_source","source_observed_at":"2026-08-03T08:15:35.523537Z"},"links":{"cited_paper":"/paper/2406.14541","citing_paper":"/paper/2601.17717"},"observation_digest":"sha256:df0b46a3fb732452a0c6a537fee4cc55436b695dfea96802a8190679592d2cfe","observation_id":"57f58c39-0957-4863-bd68-d186bb4682fe","resolution":{"observed_at":"2026-08-03T08:15:35.523537Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.14541","last_updated":"2025-03-13T21:19:46Z","snapshot_observed_at":"2026-08-14T08:50:29.223702Z","submitted_at":"2024-06-20T17:52:29Z","title":"Why LLMs Are Bad at Synthetic Table Generation (and what to do about it)","version":3},"cited_work":{"arxiv_id":"2406.14541","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2406.14541","snapshot_observed_at":"2026-07-03T20:18:55.668544Z","title":"Are llms naturally good at synthetic tabular data generation?arXiv preprint arXiv:2406.14541, 2024d","venue":null,"work_id":"a61938e5-e781-423b-b1c6-5ddab6cd28f3","year":2024},"citing_paper":{"arxiv_id":"2607.01305","last_updated":"2026-07-01T16:37:49Z","snapshot_observed_at":"2026-07-07T00:06:54.595410Z","submitted_at":"2026-07-01T16:37:49Z","title":"Generative AI and Federated Learning for Intrusion Detection Systems: A Survey","version":1},"reference_index":127,"source":"pdf_text","source_observed_at":"2026-07-03T20:18:02.667339Z"},"links":{"cited_paper":"/paper/2406.14541","citing_paper":"/paper/2607.01305"},"observation_digest":"sha256:3167317ade95344eeaa2ed0384df6dc94a7f2e08162127ff341cb07b4f4d5779","observation_id":"59d62b5c-6fc8-4562-b7b4-f0768e8afb5e","resolution":{"observed_at":"2026-07-03T20:18:55.671386Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.14541","last_updated":"2025-03-13T21:19:46Z","snapshot_observed_at":"2026-08-14T08:50:29.223702Z","submitted_at":"2024-06-20T17:52:29Z","title":"Why LLMs Are Bad at Synthetic Table Generation (and what to do about it)","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.14541","snapshot_observed_at":"2026-08-04T19:14:36.528791Z","title":"arXiv:2406.14541","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.01879","last_updated":"2026-08-03T08:24:35Z","snapshot_observed_at":"2026-08-11T13:29:20.050672Z","submitted_at":"2026-08-03T08:24:35Z","title":"LAB-Tab: LLM-Augmented Bayesian Network Adaptation for Few-Shot Tabular Generation","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-04T19:14:36.528791Z"},"links":{"cited_paper":"/paper/2406.14541","citing_paper":"/paper/2608.01879"},"observation_digest":"sha256:5e2db1142bff6be14bb405753de048ca0fb79992847752357d83816c6716c024","observation_id":"19cf0ab1-7119-4498-b649-1c08585eaf15","resolution":{"observed_at":"2026-08-04T19:14:36.528791Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2406.14541/citation-record","integrity":"/paper/2406.14541/integrity","json":"/paper/2406.14541/citation-record.json","paper":"/paper/2406.14541"},"outbound":[],"paper":{"arxiv_id":"2406.14541","last_updated":"2025-03-13T21:19:46Z","latest_version":3,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-14T08:50:29.223702Z","submitted_at":"2024-06-20T17:52:29Z","title":"Why LLMs Are Bad at Synthetic Table Generation (and what to do about it)"},"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":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2406.14541."}