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Paper Citation Record · LEDGER

Achieving Fairness in Dermatological Disease Diagnosis through Automatic Weight Adjusting Federated Learning and Personalization

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2208.11187.

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

pith.paper-citation-record.v1
2208.11187 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 2026-08-07T13:45:21.109483Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T13:19:14.515355Z

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 afc55310-fa90-4aa6-8d13-914b9feee17d · inbound

Fairness in Federated Learning: Fairness for Whom? cites this paper.

Fairness in Federated Learning: Fairness for Whom? Achieving Fairness in Dermatological Disease Diagnosis through Automatic Weight Adjusting Federated Learning and Personalization

Reference 100

Resolution
unresolved
no resolver link, observed 2026-08-07T13:45:21.109483Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:45:21.109483Z digest=sha256:2be793d0185f31825ab4658e8fb37f84acfe3a2b888893b788f6ee437600c5d3

Observation 7e8e6ab4-2f3f-4740-a2f7-e18af1e2c4b2 · inbound

Enhancing Fairness in Skin Lesion Classification for Medical Diagnosis Using Prune Learning cites this paper.

Enhancing Fairness in Skin Lesion Classification for Medical Diagnosis Using Prune Learning Achieving Fairness in Dermatological Disease Diagnosis through Automatic Weight Adjusting Federated Learning and Personalization

Reference 39

Resolution
verified exact
local_arxiv, observed 2026-08-05T13:19:14.590450Z

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=2026-08-05T13:19:12.587752Z digest=sha256:81c25acac5feed8e20c6e406d949e708a00b678582584394304050bdef0018da