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Paper Citation Record · LEDGER

A Principled Approach to Data Valuation for Federated Learning

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2009.06192.

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

pith.paper-citation-record.v1
2009.06192 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 2026-08-07T00:56:03.198958Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T20:41:09.428336Z

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 46af0a37-9c5f-404c-b23e-baa5d6b53c92 · inbound

Semivalue-based data valuation is arbitrary and gameable cites this paper.

Semivalue-based data valuation is arbitrary and gameable A Principled Approach to Data Valuation for Federated Learning

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-07T00:56:03.198958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:56:03.198958Z digest=sha256:5c4a747ae4aa2c38fdd7a64135bd2d9f9c1ac01d2de3dbf0ad7db99aa04eea8c

Observation e19a064c-2dea-4cf6-b083-9f4cafba1c70 · inbound

Enhanced Privacy and Communication Efficiency in Non-IID Federated Learning with Adaptive Quantization and Differential Privacy cites this paper.

Enhanced Privacy and Communication Efficiency in Non-IID Federated Learning with Adaptive Quantization and Differential Privacy A Principled Approach to Data Valuation for Federated Learning

Reference 45

Resolution
verified exact
arxiv_id, observed 2026-05-11T20:41:09.431761Z

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=2026-05-08T08:24:14.745888Z digest=sha256:e0fbf78ca5c8bfdb273af1f6813f446b0cc5561229c6b84efb0f387942b986bb