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Paper Citation Record · LEDGER

AI Fairness via Domain Adaptation

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2104.01109.

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

pith.paper-citation-record.v1
2104.01109 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 2026-08-11T06:34:44.6726+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:35:25.671187Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T20:35:25.983548Z

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 e4b5c564-ed27-4e31-aade-dad9f6ab51b9 · inbound

Mitigating Algorithmic Bias in Multiclass CNN Classifications Using Causal Modeling cites this paper.

Mitigating Algorithmic Bias in Multiclass CNN Classifications Using Causal Modeling AI Fairness via Domain Adaptation

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-08-10T20:35:25.990185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T20:35:25.671187Z digest=sha256:a2c690ca4dc5b8585fdb1ad127fd91ae48a4c51efa741b5b592da1c3c621aa59

Observation 06f7ea01-7ba3-4d5b-be4e-490887902841 · inbound

Practitioner Insights on Fairness Requirements in the AI Development Life Cycle: An Interview Study cites this paper.

Practitioner Insights on Fairness Requirements in the AI Development Life Cycle: An Interview Study AI Fairness via Domain Adaptation

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-03T16:22:54.449066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T16:22:54.449066Z digest=sha256:902935c6489277f5cc3313d914abda73b30727128d53bb63c6e2a49818cdd3ab