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Paper Citation Record · LEDGER

Handling Inter-class and Intra-class Imbalance in Class-imbalanced Learning

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2111.12791.

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

pith.paper-citation-record.v1
2111.12791 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:56:16.153294Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T00:57:30.739967Z

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 972973dc-3b41-4a91-85bb-d01a9fc5e430 · inbound

Dusty stellar sources classification by implementing machine learning methods based on spectroscopic observations in the Magellanic Clouds cites this paper.

Dusty stellar sources classification by implementing machine learning methods based on spectroscopic observations in the Magellanic Clouds Handling Inter-class and Intra-class Imbalance in Class-imbalanced Learning

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-16T11:56:16.153294Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T11:56:16.153294Z digest=sha256:1d508fdde5675f1595a2901b7b1ee31b8d1ad41f4117ee639c2377af9e53df4a

Observation a01166f3-314c-4240-b739-3a68de7f94a5 · inbound

Compositional Attribute Imbalance in Vision Datasets cites this paper.

Compositional Attribute Imbalance in Vision Datasets Handling Inter-class and Intra-class Imbalance in Class-imbalanced Learning

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-15T19:57:49.301381Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:57:49.301381Z digest=sha256:1c842f273a93f6942900840afd2da09bfa06330c116865c2fce62aae5d4e420c

Observation 1a2b3e5a-3e63-464e-afe4-0113b03f87dc · inbound

Multi-Level Analyzation of Imbalance to Resolve Non-IID-Ness in Federated Learning cites this paper.

Multi-Level Analyzation of Imbalance to Resolve Non-IID-Ness in Federated Learning Handling Inter-class and Intra-class Imbalance in Class-imbalanced Learning

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-07-03T00:57:30.741615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-27T16:51:20.071589Z digest=sha256:f15a6ad26a57ae45c3ae068e2225b6002aea4c3c086813c627b3e622afb94c25