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Paper Citation Record · LEDGER

Deep Long-Tailed Learning: A Survey

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2110.04596.

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

pith.paper-citation-record.v1
2110.04596 v2

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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T05:28:44.367857Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-08T19:33:21.635901Z

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 c2a3112f-a238-4c0b-bf5f-69cd02330959 · inbound

Long-tailed Medical Diagnosis with Relation-aware Representation Learning and Iterative Classifier Calibration cites this paper.

Long-tailed Medical Diagnosis with Relation-aware Representation Learning and Iterative Classifier Calibration Deep Long-Tailed Learning: A Survey

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-09T05:28:44.367857Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T05:28:44.367857Z digest=sha256:304d39b4de0dad0e37c1767b3af48a0c617862549400c3437a9b2e6b821e9285

Observation b5ad75d7-7e3d-4b4c-a092-760036413861 · inbound

A Novel Convolutional-Free Method for 3D Medical Imaging Segmentation cites this paper.

A Novel Convolutional-Free Method for 3D Medical Imaging Segmentation Deep Long-Tailed Learning: A Survey

Reference 49

Resolution
verified exact
local_arxiv, observed 2026-08-08T19:33:21.641886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T19:33:21.533848Z digest=sha256:8f1239baaf49e4a5cfe8af712d9ce360cf8821a510474deb2967a2df0140025f