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Paper Citation Record · LEDGER

A Comparison of Synthetic Oversampling Methods for Multi-class Text Classification

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2008.04636.

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

pith.paper-citation-record.v1
2008.04636 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 2026-08-07T11:30:34.776194Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T14:41:41.577764Z

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 4db492bb-dea4-4a06-b28b-22a858a169be · inbound

Data Balancing Strategies: A Systematic Survey of Resampling and Augmentation Methods cites this paper.

Data Balancing Strategies: A Systematic Survey of Resampling and Augmentation Methods A Comparison of Synthetic Oversampling Methods for Multi-class Text Classification

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-22T14:41:41.580689Z

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=2026-05-22T14:37:46.556390Z digest=sha256:cb315bfcffd27ccafb38390b8d5ca106c7048044d18e581af0939d77b1235c55

Observation 8a77755b-72d4-42b0-a094-1d2da15a2d6e · inbound

Approximate Borderline Sampling using Granular-Ball for Classification Tasks cites this paper.

Approximate Borderline Sampling using Granular-Ball for Classification Tasks A Comparison of Synthetic Oversampling Methods for Multi-class Text Classification

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-07T11:30:34.776194Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:30:34.776194Z digest=sha256:e5f827b6b360e2acec9dcb99e9d1af2402d66a55ec7a222f6090314d532cd397