Paper Citation Record · LEDGER

Language Models are Realistic Tabular Data Generators

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 22 inbound Pith citation observations for arXiv:2210.06280.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2210.06280 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 22 of 22 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:27:16.017672Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-03T20:58:57.943567Z

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 a5e86a8a-e521-4f07-ac7d-bdd7a8fc7473 · 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 Language Models are Realistic Tabular Data Generators

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-23T06:05:28.007816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation e8603b13-45e3-40a8-9f62-32360c376c0a · inbound

Evaluating Inter-Column Logical Relationships in Synthetic Tabular Data Generation cites this paper.

Evaluating Inter-Column Logical Relationships in Synthetic Tabular Data Generation Language Models are Realistic Tabular Data Generators

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-23T04:15:22.821180Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 47ebc4f0-ce5b-4f8c-97a6-1625b353953b · inbound

FASTGEN: Fast and Cost-Effective Synthetic Tabular Data Generation with LLMs cites this paper.

FASTGEN: Fast and Cost-Effective Synthetic Tabular Data Generation with LLMs Language Models are Realistic Tabular Data Generators

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T15:27:16.017672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 860cb0de-8298-4042-9ad2-f6248ad280c4 · inbound

Tab-MIA: A Benchmark Dataset for Membership Inference Attacks on Tabular Data in LLMs cites this paper.

Tab-MIA: A Benchmark Dataset for Membership Inference Attacks on Tabular Data in LLMs Language Models are Realistic Tabular Data Generators

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T14:58:05.260401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b00bed98-18b0-453d-84be-feae0156aac7 · inbound

Accept or Deny? Evaluating LLM Fairness and Performance in Loan Approval across Table-to-Text Serialization Approaches cites this paper.

Accept or Deny? Evaluating LLM Fairness and Performance in Loan Approval across Table-to-Text Serialization Approaches Language Models are Realistic Tabular Data Generators

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-05T14:21:45.474882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1396e9d5-2d71-4c0a-ba7d-91b3b105e94e · inbound

Meta-learning ecological priors from large language models explains human learning and decision making cites this paper.

Meta-learning ecological priors from large language models explains human learning and decision making Language Models are Realistic Tabular Data Generators

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-05T14:46:34.721518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa5d25b6-188b-4a48-bd0d-2c1c5caeecf4 · inbound

TAGAL: Tabular Data Generation using Agentic LLM Methods cites this paper.

TAGAL: Tabular Data Generation using Agentic LLM Methods Language Models are Realistic Tabular Data Generators

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-05T10:23:22.430718Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c9d5fe93-e36c-48d5-8151-9d56ea30127c · inbound

Ensembling Membership Inference Attacks Against Tabular Generative Models cites this paper.

Ensembling Membership Inference Attacks Against Tabular Generative Models Language Models are Realistic Tabular Data Generators

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-05T11:32:55.983111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b4b893d-6ee0-4f10-8240-41d334798fef · inbound

When Tables Leak: Attacking String Memorization in LLM-Based Tabular Data Generation cites this paper.

When Tables Leak: Attacking String Memorization in LLM-Based Tabular Data Generation Language Models are Realistic Tabular Data Generators

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-16T23:48:41.864964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 2a816744-71a5-4741-af54-8d72c4a8eaa8 · 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 Language Models are Realistic Tabular Data Generators

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T08:15:13.774372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 198e1598-1c49-43c5-a211-6ea1b453d191 · inbound

AnomalyVFM -- Transforming Vision Foundation Models into Zero-Shot Anomaly Detectors cites this paper.

AnomalyVFM -- Transforming Vision Foundation Models into Zero-Shot Anomaly Detectors Language Models are Realistic Tabular Data Generators

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-16T10:47:45.453001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation cca0ce04-d377-4ab8-b716-aa4b4ba21b18 · inbound

From Noise to Order: Learning to Rank via Denoising Diffusion cites this paper.

From Noise to Order: Learning to Rank via Denoising Diffusion Language Models are Realistic Tabular Data Generators

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-03T00:10:45.622152Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07c17369-5c35-4734-bf57-c6b1a7fda7c6 · inbound

Self-Improving Tabular Language Models via Iterative Reward-Guided Post-Training cites this paper.

Self-Improving Tabular Language Models via Iterative Reward-Guided Post-Training Language Models are Realistic Tabular Data Generators

Reference 17

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T12:46:04.005475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation ef3038b3-3e64-466c-9f1e-77b93e7c8776 · inbound

The Power of Order: Fooling LLMs with Adversarial Table Permutations cites this paper.

The Power of Order: Fooling LLMs with Adversarial Table Permutations Language Models are Realistic Tabular Data Generators

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-11T15:36:06.373211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 8245051c-6c43-45ec-8896-817d2a1ceb6c · inbound

The Power of Order: Fooling LLMs with Adversarial Table Permutations cites this paper.

The Power of Order: Fooling LLMs with Adversarial Table Permutations Language Models are Realistic Tabular Data Generators

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-12T02:26:16.582448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 54b079e2-ebd9-4cd5-91da-5b44db407ae4 · inbound

Breaking the Quality-Privacy Tradeoff in Tabular Data Generation via In-Context Learning cites this paper.

Breaking the Quality-Privacy Tradeoff in Tabular Data Generation via In-Context Learning Language Models are Realistic Tabular Data Generators

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-09T06:25:45.740589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation bc708191-d6dc-4706-9ff8-1939b023ca87 · inbound

LLM-Driven Performance-Space Augmentation for Meta-Learning-Based Algorithm Selection cites this paper.

LLM-Driven Performance-Space Augmentation for Meta-Learning-Based Algorithm Selection Language Models are Realistic Tabular Data Generators

Reference 14

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T07:06:36.751436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 89979e99-2ce0-4f8a-9cef-5d6da19a1709 · inbound

Concordia: Self-Improving Synthetic Tables for Federated LLMs cites this paper.

Concordia: Self-Improving Synthetic Tables for Federated LLMs Language Models are Realistic Tabular Data Generators

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-12T06:16:27.611678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation d76242ae-869d-4e66-b080-378097e83ebb · inbound

Concordia: Self-Improving Synthetic Tables for Federated LLMs cites this paper.

Concordia: Self-Improving Synthetic Tables for Federated LLMs Language Models are Realistic Tabular Data Generators

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-20T22:23:47.865667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation ba801b89-df7c-4f3b-838e-9f3d8fcba110 · inbound

Categorical Prior Lock-in: Why In-Context Learning Fails for Structured Data cites this paper.

Categorical Prior Lock-in: Why In-Context Learning Fails for Structured Data Language Models are Realistic Tabular Data Generators

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-07-03T10:07:56.182665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation c7206674-345c-4048-baa8-6ffb09d183bb · inbound

PSyGenTAB: A Privacy-Preserving Framework for Synthetic Clinical Tabular Data Generation via Constrained Optimization cites this paper.

PSyGenTAB: A Privacy-Preserving Framework for Synthetic Clinical Tabular Data Generation via Constrained Optimization Language Models are Realistic Tabular Data Generators

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-07-03T20:58:57.945809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 687d6087-fa36-46ae-857d-e440169a8214 · inbound

FairDiffuseVQVAE: Sampling-Time Fairness in Tabular Diffusion via Conditional Refinement of Vector-Quantized Latents cites this paper.

FairDiffuseVQVAE: Sampling-Time Fairness in Tabular Diffusion via Conditional Refinement of Vector-Quantized Latents Language Models are Realistic Tabular Data Generators

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T16:50:34.480982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.