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Paper Citation Record · LEDGER

Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2403.06017.

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

pith.paper-citation-record.v1
2403.06017 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 2026-08-16T06:30:59.297886+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:31:25.355044Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T16:38:28.560832Z

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 99030d10-8294-4b1e-81d5-d534b74da175 · inbound

Towards Fair Graph Neural Networks via Graph Counterfactual without Sensitive Attributes cites this paper.

Towards Fair Graph Neural Networks via Graph Counterfactual without Sensitive Attributes Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark

Reference 36

Resolution
verified exact
local_arxiv, observed 2026-08-11T16:38:28.611678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-11T16:38:28.176642Z digest=sha256:be7e0024c55431b2a44da4db6bc86a10c5cdc8ef874a7e00ca24045f0beee493

Observation 23e613c1-a67b-40df-bc58-303e832a73b4 · inbound

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing cites this paper.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-15T21:31:25.355044Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:31:25.355044Z digest=sha256:e25f26724abefd0a04560bca94ec7b8ff1fdc1afe982df3742d5c4a9826d1b6e