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Paper Citation Record · LEDGER

Data Augmentation with Variational Autoencoder for Imbalanced Dataset

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2412.07039.

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

pith.paper-citation-record.v1
2412.07039 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:19:20.981785Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T19:16:28.911802Z

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 4a26f8a2-2a96-441b-903b-37ef91d4830a · inbound

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

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.

source=pdf_text observed=2026-08-07T11:19:20.981785Z digest=sha256:1b3f0f7ac8b9a922f9e52a0f6989e7eb417c69baad9ef5743525a7357988e373

Observation f4218719-20f4-42b5-8d9a-a2fc1056584c · inbound

Taming Data Challenges in ML-based Security Tasks Using Generative AI cites this paper.

Taming Data Challenges in ML-based Security Tasks Using Generative AI Data Augmentation with Variational Autoencoder for Imbalanced Dataset

Reference 94

Resolution
verified exact
local_arxiv, observed 2026-08-06T19:16:28.919512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T19:16:28.688967Z digest=sha256:b975c155506e9b12e481a7408fc874baea80ec2160439d0cea3ff988c08a47eb