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Paper Citation Record · LEDGER

Modeling Tabular data using Conditional GAN

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 18 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 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 18 of 18 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:19:21.377871Z

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

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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

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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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-23T06:08:04.748815Z digest=sha256:13cbd8a421ab053fa4eba6c36234a42f06f349f3b7a23ac3c14a21f12deac7aa

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:19:21.377871Z digest=sha256:2d21186709420b25b6ac6af34bf973cc7f54de9ce6e4f57807d577bfecd5a8c5

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:50:38.970284Z digest=sha256:7e42c6349fba13a99ea90bb6e367e9391227f91a36be8deb22bf7ba343d9c41f

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:31:07.380146Z digest=sha256:263827e632f8343e5ee2a76caa23f0a46d47494024bbe74f96cbf3e8281418a7

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-18T22:23:30.976172Z digest=sha256:72605e72ba0e7b43f31628dbf68ec0f62d505dc9210aa27f90ba1343b151271c

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T16:48:09.082750Z digest=sha256:10c8308d3762a718df859e420b3314febda4019d385464ad458e9b30bd41ecd0

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.

source=pdf_text observed=2026-08-05T14:23:13.750540Z digest=sha256:06894e0dea870ed56b194a2de5b9f40eb76f44afcd8d5ab36297141b7ebeb549

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.

source=pdf_text observed=2026-08-05T14:23:20.216555Z digest=sha256:0a1dd49d9bcd89bb50ac33c1bee89ada93f8c5c106c49ee3d70d6aeea5f01679

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-21T21:10:05.466845Z digest=sha256:589094802829811ad9f3bcfe921d15c74a7290a147e464941ff1ceb80eec96cf

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.

source=arxiv_source observed=2026-08-03T08:15:35.435351Z digest=sha256:e3821037e2b39bba757fd939e6d45b35b97e4d43083dec8bb733d93f79adefd6

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-08T08:53:25.483782Z digest=sha256:c5f60f581345c9dcdfcc90b24063e9eaa8c68e39f2eb3844c95ceecda427528c

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-25T04:39:07.498461Z digest=sha256:42e167487352e01b7c34146c6cab4092be3449b95a278ccbdfe6049e515dc9d3

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-30T16:05:21.900148Z digest=sha256:1f3a7feb8662e285c818a93f2fcc9fe268a1c2a1a9ab45603f83324095cb0f93

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

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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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-28T20:31:27.240707Z digest=sha256:06274871b5e66de8e8f0df935b74b6acb1f340cc262846823121f3a0b853d4e6

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-28T07:05:18.026601Z digest=sha256:ebc0ff47feaaf3615f10789b969ec9063c334f98d507a5fdc723356214d1d552

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-27T10:14:07.904158Z digest=sha256:f28178f272271164d47d2f8a481c8e45693c507a30091ab67e3672fd95e22e26

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-07-01T06:35:06.822132Z digest=sha256:fed11de953c54c2768d7eb3d8a2efdd68a899bd2209fb16de4666b0eaa5b5681

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.

source=arxiv_source observed=2026-08-03T16:50:39.504894Z digest=sha256:1bb3e6efe3c46f116f1e383acff7ac7181a6fa14995978b846c0998d4d1af0e6