Paper Citation Record · LEDGER

Modeling Tabular data using Conditional GAN

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 19 inbound Pith citation observations for arXiv:1907.00503.

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

pith.paper-citation-record.v1
1907.00503 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 19 of 19 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T16:49:24.909152Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
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malformed identifier0
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External citation measurements

94
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation c3a3909f-08cd-4bb9-b6dd-d7327ea5c855 · inbound

Can Synthetic Data be Fair and Private? A Comparative Study of Synthetic Data Generation and Fairness Algorithms cites this paper.

Can Synthetic Data be Fair and Private? A Comparative Study of Synthetic Data Generation and Fairness Algorithms Modeling Tabular data using Conditional GAN

Reference 55

Resolution: verified exact; arxiv_id, observed 2026-05-23T06:12:39.021760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 52b5f830-ec59-4368-8425-672215c88bf5 · inbound

CARTGen-IR: Synthetic Tabular Data Generation for Imbalanced Regression cites this paper.

CARTGen-IR: Synthetic Tabular Data Generation for Imbalanced Regression Modeling Tabular data using Conditional GAN

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T11:19:21.377871Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 53807c61-57ef-4b14-ad9a-3bdb476d6c43 · inbound

CopulaSMOTE: A Copula-Based Oversampling Approach for Imbalanced Classification in Diabetes Prediction cites this paper.

CopulaSMOTE: A Copula-Based Oversampling Approach for Imbalanced Classification in Diabetes Prediction Modeling Tabular data using Conditional GAN

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-06T23:50:38.970284Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7880709-4b72-4f1d-a2dc-0c9009a5e276 · inbound

Pre-, In-, and Post-Processing Class Imbalance Mitigation Techniques for Failure Detection in Optical Networks cites this paper.

Pre-, In-, and Post-Processing Class Imbalance Mitigation Techniques for Failure Detection in Optical Networks Modeling Tabular data using Conditional GAN

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T16:31:07.380146Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23725517-c069-439b-bce5-a02ba0c4bce2 · inbound

Cross-Flow Correlations Survive Synthesis: Measuring Source-Level Privacy Leakage in Synthetic Network Traces cites this paper.

Cross-Flow Correlations Survive Synthesis: Measuring Source-Level Privacy Leakage in Synthetic Network Traces Modeling Tabular data using Conditional GAN

Reference 6

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T22:26:53.234393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 921756de-522c-40d3-a4c4-60d45b71a7b4 · inbound

From Data to Decision: A Multi-Stage Framework for Class Imbalance Mitigation in Optical Network Failure Analysis cites this paper.

From Data to Decision: A Multi-Stage Framework for Class Imbalance Mitigation in Optical Network Failure Analysis Modeling Tabular data using Conditional GAN

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-05T16:48:09.082750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d41c933c-123e-4a2c-8c47-e81ec39c7d35 · inbound

Friend or Foe cites this paper.

Friend or Foe Modeling Tabular data using Conditional GAN

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-05T14:23:13.750540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a2c534f4-6fd9-487b-aadd-577881027b0c · inbound

Beyond Synthetic Augmentation: Group-Aware Threshold Calibration for Robust Balanced Accuracy in Imbalanced Learning cites this paper.

Beyond Synthetic Augmentation: Group-Aware Threshold Calibration for Robust Balanced Accuracy in Imbalanced Learning Modeling Tabular data using Conditional GAN

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-05T14:23:20.216555Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 528604c0-cd3a-43e8-a700-c46ca4fa80ba · inbound

Quality Degradation Attack in Synthetic Data cites this paper.

Quality Degradation Attack in Synthetic Data Modeling Tabular data using Conditional GAN

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-21T21:10:38.542670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 75607702-ac2e-4932-9862-6a4d1b217823 · 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 Modeling Tabular data using Conditional GAN

Reference 243

Resolution: unresolved; no resolver link, observed 2026-08-03T08:15:35.435351Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation de97f6c5-488e-4c91-9703-64e0e463c0d2 · inbound

COMPASS: A Unified Decision-Intelligence System for Navigating Performance Trade-off in HPC cites this paper.

COMPASS: A Unified Decision-Intelligence System for Navigating Performance Trade-off in HPC Modeling Tabular data using Conditional GAN

Reference 130

Resolution: verified exact; arxiv_id, observed 2026-05-08T22:29:19.364710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7ce756b5-16b8-48d2-88ad-7c464bb71547 · inbound

Class-Dependent Hybrid Data Augmentation for Multiclass Migraine Classification under Severe Class Imbalance cites this paper.

Class-Dependent Hybrid Data Augmentation for Multiclass Migraine Classification under Severe Class Imbalance Modeling Tabular data using Conditional GAN

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-25T04:40:23.571997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a07928dd-6f5a-49d5-aba3-9ca1cb0961fb · inbound

Class-Dependent Hybrid Data Augmentation for Multiclass Migraine Classification under Severe Class Imbalance cites this paper.

Class-Dependent Hybrid Data Augmentation for Multiclass Migraine Classification under Severe Class Imbalance Modeling Tabular data using Conditional GAN

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-06-30T16:14:53.720196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3850230f-3860-4757-ab29-d45cb15342d8 · inbound

Context-Conditioned Generative Models Enable Subnational Refinement of Sparse Humanitarian Surveys cites this paper.

Context-Conditioned Generative Models Enable Subnational Refinement of Sparse Humanitarian Surveys Modeling Tabular data using Conditional GAN

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-06-28T20:32:36.642321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 148ab773-c1d4-4e5e-abe6-a58dc39cbff5 · inbound

Toward Calibrated, Fair, and accurate Deepfake Detection cites this paper.

Toward Calibrated, Fair, and accurate Deepfake Detection Modeling Tabular data using Conditional GAN

Reference 147

Resolution: verified exact; arxiv_id, observed 2026-06-28T07:11:44.886378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2fa71dce-4526-4dc6-947b-4920e24162ef · 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 Modeling Tabular data using Conditional GAN

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-07-03T10:07:56.165508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 0e436b65-9e99-459f-a0e9-3f23be7ebc90 · inbound

Sequential RC-TGAN: Generating Relational Time Series with Spectral Envelope Loss cites this paper.

Sequential RC-TGAN: Generating Relational Time Series with Spectral Envelope Loss Modeling Tabular data using Conditional GAN

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T06:35:29.336901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4cb02603-25dd-42cb-bc90-72ff2ade39af · 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 Modeling Tabular data using Conditional GAN

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-03T16:50:39.504894Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c36513c0-dc49-42dc-b74a-96e346d59fac · inbound

Evaluating Machine Learning Models for Post-Wildfire Debris-Flow Prediction cites this paper.

Evaluating Machine Learning Models for Post-Wildfire Debris-Flow Prediction Modeling Tabular data using Conditional GAN

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-08T16:49:24.909152Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.