Paper Citation Record · LEDGER

CARTGen-IR: Synthetic Tabular Data Generation for Imbalanced Regression

As of 8 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2506.02811.

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

pith.paper-citation-record.v1
2506.02811 v2

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

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

measured 29 of 29 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

29 of 29 outbound references displayed

verified exact0
verified fuzzy24
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cb616d3f-6a08-4377-b6e0-d73b095b9904 · outbound

This paper cites JMIR Medical Informatics12, e55118 (2024).

CARTGen-IR: Synthetic Tabular Data Generation for Imbalanced Regression JMIR Medical Informatics12, e55118 (2024)

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:19:27.075506Z

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.

Observation c0361f34-a144-4c42-bfcf-9f16d01b96cd · outbound

This paper cites Remote Sensing of Environment281, 113220 (2022).

CARTGen-IR: Synthetic Tabular Data Generation for Imbalanced Regression Remote Sensing of Environment281, 113220 (2022)

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:19:26.808824Z

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.

Observation a71f393b-7943-464c-a045-b9edb626e761 · outbound

This paper cites Expert Systems with Applica- tions252, 124118 (2024).

CARTGen-IR: Synthetic Tabular Data Generation for Imbalanced Regression Expert Systems with Applica- tions252, 124118 (2024)

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:19:26.513830Z

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.

Observation b1cfb7eb-879c-42b8-aa9d-27d364cf8198 · outbound

This paper cites ACM Computing Surveys49, Article 31 (2016).

CARTGen-IR: Synthetic Tabular Data Generation for Imbalanced Regression ACM Computing Surveys49, Article 31 (2016)

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:19:26.249150Z

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.

Observation 3cd262bc-c9e5-4dd3-9a41-b355a020fa47 · outbound

This paper cites In: Proceedings of the 1st International Workshop on Learning with Imbalanced Domains: Theory and Applications.

CARTGen-IR: Synthetic Tabular Data Generation for Imbalanced Regression In: Proceedings of the 1st International Workshop on Learning with Imbalanced Domains: Theory and Applications

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:19:25.938603Z

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.

Observation 7289c2f9-00f9-462a-ade2-f9e391b10205 · outbound

This paper cites Neurocomputing343, 76–99 (2019).

CARTGen-IR: Synthetic Tabular Data Generation for Imbalanced Regression Neurocomputing343, 76–99 (2019)

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:19:25.704611Z

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.

Observation 2f34f932-ff21-4207-b555-e1694865d0f3 · outbound

This paper cites Version 0.1.6, available via PyPI (2025) 14 A.

CARTGen-IR: Synthetic Tabular Data Generation for Imbalanced Regression Version 0.1.6, available via PyPI (2025) 14 A

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:19:25.507043Z

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.

Observation b250e4b5-6ed2-486c-acbb-33eea1bcb1b8 · outbound

This paper cites Chapman, New York (1984).

CARTGen-IR: Synthetic Tabular Data Generation for Imbalanced Regression Chapman, New York (1984)

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:19:25.226528Z

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.

Observation 2e139939-11cf-4185-940d-4b4293df874f · outbound

This paper cites an unresolved cited work.

CARTGen-IR: Synthetic Tabular Data Generation for Imbalanced Regression Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-07T11:19:25.043868Z

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.

Observation 03628e1e-6e48-4771-b93d-51a9d39c50f9 · outbound

This paper cites Expert Systems with Applications193, 116387 (2022).

CARTGen-IR: Synthetic Tabular Data Generation for Imbalanced Regression Expert Systems with Applications193, 116387 (2022)

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:19:24.817510Z

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.

Observation c4ffb69b-35e7-42da-b7b9-d2560463b3d1 · outbound

This paper cites Applied Intelligence54, 8789–8799 (2024).

CARTGen-IR: Synthetic Tabular Data Generation for Imbalanced Regression Applied Intelligence54, 8789–8799 (2024)

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:19:24.631464Z

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.

Observation 497e1541-c29a-41a0-9640-b27a56d9289d · outbound

This paper cites JAIR16, 321–357 (2002).

CARTGen-IR: Synthetic Tabular Data Generation for Imbalanced Regression JAIR16, 321–357 (2002)

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:19:24.507540Z

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.

Observation 6b62722d-45ee-4116-be2b-07f4441cfdb3 · outbound

This paper cites In: IEEE International Joint Conference on Neural Networks.

CARTGen-IR: Synthetic Tabular Data Generation for Imbalanced Regression In: IEEE International Joint Conference on Neural Networks

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:19:24.341760Z

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.

Observation ecca572b-2995-470a-9675-100df9f3c442 · outbound

This paper cites Com- putational Statistics & Data Analysis52, 5186–5201 (2008).

CARTGen-IR: Synthetic Tabular Data Generation for Imbalanced Regression Com- putational Statistics & Data Analysis52, 5186–5201 (2008)

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:19:24.166467Z

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.

Observation bf11d232-6dfb-4648-a6b4-424220444a88 · outbound

This paper cites In: Proceedings of the 40th International Con- ference on Machine Learning (ICML’23).

CARTGen-IR: Synthetic Tabular Data Generation for Imbalanced Regression In: Proceedings of the 40th International Con- ference on Machine Learning (ICML’23)

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:19:24.016188Z

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.

Observation ab200f65-beec-47ed-8821-2c9ef42baacf · outbound

This paper cites Scientific Reports12(2022).

CARTGen-IR: Synthetic Tabular Data Generation for Imbalanced Regression Scientific Reports12(2022)

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:19:23.823295Z

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.

Observation 69904f84-4bee-4ce9-a0a7-b5f01026954f · outbound

This paper cites Processes12, 375 (2024).

CARTGen-IR: Synthetic Tabular Data Generation for Imbalanced Regression Processes12, 375 (2024)

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:19:23.542941Z

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.

Observation 1a6e1cd2-615a-4215-a2f5-fd28787971b4 · outbound

This paper cites Synthetic Tabular Data Generation for Class Imbalance and Fairness: A Comparative Study.

CARTGen-IR: Synthetic Tabular Data Generation for Imbalanced Regression Synthetic Tabular Data Generation for Class Imbalance and Fairness: A Comparative Study

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T11:19:20.060092Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da7d06b5-d7f9-4153-9ac4-2452b86b72fa · outbound

This paper cites In: 2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA).

CARTGen-IR: Synthetic Tabular Data Generation for Imbalanced Regression In: 2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA)

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:19:23.333674Z

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.

Observation 5fc82840-94ca-4448-b382-7425335984cb · outbound

This paper cites Jour- nal of Official Statistics21(2005).

CARTGen-IR: Synthetic Tabular Data Generation for Imbalanced Regression Jour- nal of Official Statistics21(2005)

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:19:23.043189Z

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.

Observation e09b23a9-b1b4-41f0-8124-c65db7c9fde2 · outbound

This paper cites Department of Computer Science, Faculty of Sciences, University of Porto (2011).

CARTGen-IR: Synthetic Tabular Data Generation for Imbalanced Regression Department of Computer Science, Faculty of Sciences, University of Porto (2011)

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:19:22.841623Z

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.

Observation 8e9d6d7b-314e-47a8-be0e-d23f8d5342e9 · outbound

This paper cites Ma- chine Learning109, 1803–1835 (2020).

CARTGen-IR: Synthetic Tabular Data Generation for Imbalanced Regression Ma- chine Learning109, 1803–1835 (2020)

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:19:22.577781Z

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.

Observation 1323a1f3-263e-4eb3-8539-78565ea5f604 · outbound

This paper cites Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences379(2021).

CARTGen-IR: Synthetic Tabular Data Generation for Imbalanced Regression Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences379(2021)

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:19:22.355631Z

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.

Observation b7f347bb-ae78-48c2-9f71-ba5f11ff67cf · outbound

This paper cites Machine Learning110, 2187–2211 (2021).

CARTGen-IR: Synthetic Tabular Data Generation for Imbalanced Regression Machine Learning110, 2187–2211 (2021)

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T11:19:20.815132Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a26f8a2-2a96-441b-903b-37ef91d4830a · outbound

This paper cites Data Augmentation with Variational Autoencoder for Imbalanced Dataset.

CARTGen-IR: Synthetic Tabular Data Generation for Imbalanced Regression Data Augmentation with Variational Autoencoder for Imbalanced Dataset

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T11:19:20.981785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2112dccb-cb0a-4557-bd89-3d0378e9ed11 · outbound

This paper cites Information Sciences642, 119157 (2023).

CARTGen-IR: Synthetic Tabular Data Generation for Imbalanced Regression Information Sciences642, 119157 (2023)

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:19:22.097217Z

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.

Observation a234fd45-907c-457e-b240-aacd3c184223 · outbound

This paper cites In: Progress in Artificial Intelligence.

CARTGen-IR: Synthetic Tabular Data Generation for Imbalanced Regression In: Progress in Artificial Intelligence

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:19:21.819939Z

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.

Observation f0bc9386-90a5-4ef3-a887-64e250e22040 · outbound

This paper cites Expert Systems32, 465–476 (2015).

CARTGen-IR: Synthetic Tabular Data Generation for Imbalanced Regression Expert Systems32, 465–476 (2015)

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:19:21.620170Z

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.

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

This paper cites Modeling Tabular data using Conditional GAN.

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.

Pith citing papers

No inbound Pith citation observations are available.