Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Why LLMs Are Bad at Synthetic Table Generation (and what to do about it)
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.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T18:01:47.320448Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T20:18:55.668544Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 913bef65-6884-4e51-abe4-b7c8ed490a9f · inbound
A text-to-tabular approach to generate synthetic patient data using LLMs cites this paper.
A text-to-tabular approach to generate synthetic patient data using LLMs Why LLMs Are Bad at Synthetic Table Generation (and what to do about it)
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T20:53:46.135512Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 00d6fd29-2100-4a25-9c85-c1a8ea0b6ace · inbound
Creating Artificial Students that Never Existed: Leveraging Large Language Models and CTGANs for Synthetic Data Generation cites this paper.
Creating Artificial Students that Never Existed: Leveraging Large Language Models and CTGANs for Synthetic Data Generation Why LLMs Are Bad at Synthetic Table Generation (and what to do about it)
Reference 54
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T06:05:28.029583Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation e872ac54-9f5a-4eb2-9993-d157eb4bb346 · inbound
Making Sense of Data in the Wild: Data Analysis Automation at Scale cites this paper.
Making Sense of Data in the Wild: Data Analysis Automation at Scale Why LLMs Are Bad at Synthetic Table Generation (and what to do about it)
Reference 272
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T13:53:52.299773Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b191a34b-e9af-40b1-b0e4-21a0feb6fa85 · inbound
LLM-TabLogic: Preserving Inter-Column Logical Relationships in Synthetic Tabular Data via Prompt-Guided Latent Diffusion cites this paper.
LLM-TabLogic: Preserving Inter-Column Logical Relationships in Synthetic Tabular Data via Prompt-Guided Latent Diffusion Why LLMs Are Bad at Synthetic Table Generation (and what to do about it)
Reference 18
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T01:07:19.849460Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation ef010d32-f54d-48f5-b3e0-d4c63da37a63 · inbound
The Prompt is Mightier than the Example cites this paper.
The Prompt is Mightier than the Example Why LLMs Are Bad at Synthetic Table Generation (and what to do about it)
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:34:11.843576Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 32280136-23ac-46df-a1b8-4f9af8638021 · inbound
Dependency-aware synthetic tabular data generation cites this paper.
Dependency-aware synthetic tabular data generation Why LLMs Are Bad at Synthetic Table Generation (and what to do about it)
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T18:01:47.320448Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 57f58c39-0957-4863-bd68-d186bb4682fe · inbound
A Survey on Evaluating Quality and Trustworthiness in LLM-Generated Data cites this paper.
A Survey on Evaluating Quality and Trustworthiness in LLM-Generated Data Why LLMs Are Bad at Synthetic Table Generation (and what to do about it)
Reference 244
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T08:15:35.523537Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 59d62b5c-6fc8-4562-b7b4-f0768e8afb5e · inbound
Generative AI and Federated Learning for Intrusion Detection Systems: A Survey cites this paper.
Generative AI and Federated Learning for Intrusion Detection Systems: A Survey Why LLMs Are Bad at Synthetic Table Generation (and what to do about it)
Reference 127
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T20:18:55.671386Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 19cf0ab1-7119-4498-b649-1c08585eaf15 · inbound
LAB-Tab: LLM-Augmented Bayesian Network Adaptation for Few-Shot Tabular Generation cites this paper.
LAB-Tab: LLM-Augmented Bayesian Network Adaptation for Few-Shot Tabular Generation Why LLMs Are Bad at Synthetic Table Generation (and what to do about it)
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T19:14:36.528791Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.