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Paper Citation Record · LEDGER

The Fairness-Accuracy Pareto Front

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2008.10797.

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

pith.paper-citation-record.v1
2008.10797 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 2026-08-14T06:32:32.682623+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T12:02:40.882555Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

6
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 37de4480-68c5-44a0-8ce1-07f5e5704f72 · inbound

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence cites this paper.

Multi-Objective Reinforcement Learning for Automated Resilient Cyber Defence The Fairness-Accuracy Pareto Front

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-12T12:02:40.882555Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T12:02:40.882555Z digest=sha256:1bc024e60bae4c4877f5927ea42d491f278bdc6ab42dbb2b4a4316a6cec1fbf8

Observation 41e3bae8-1543-4d1c-a26e-f11a4b3c0e4c · inbound

Toward Calibrated, Fair, and accurate Deepfake Detection cites this paper.

Toward Calibrated, Fair, and accurate Deepfake Detection The Fairness-Accuracy Pareto Front

Reference 139

Resolution
verified exact
arxiv_id, observed 2026-06-28T07:11:44.891398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-06-28T07:05:18.026601Z digest=sha256:9dd1040f0903c692ae8166649e9a9323b38d46d4b67ab97d065e45d081db4261