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Paper Citation Record · LEDGER

Federated Communication-Efficient Multi-Objective Optimization

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2410.16398.

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

pith.paper-citation-record.v1
2410.16398 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 2026-08-13T06:32:02.005865+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T18:53:49.786267Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T18:53:51.604723Z

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 5cde34ed-c901-4e82-b847-a528de03ef40 · inbound

Gradient-Based Multi-Objective Deep Learning: Algorithms, Theories, Applications, and Beyond cites this paper.

Gradient-Based Multi-Objective Deep Learning: Algorithms, Theories, Applications, and Beyond Federated Communication-Efficient Multi-Objective Optimization

Reference 2

Resolution
verified exact
local_arxiv, observed 2026-08-10T18:53:51.609919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-10T18:53:49.786267Z digest=sha256:b1972bd0d695e2ad4d5414d2cf97503e3615c0c9d450b6d758ee314c40d14ea5

Observation 3d85ec7d-97e2-4523-9bc3-f3e7ffe71e68 · inbound

FIRM: Federated In-client Regularized Multi-objective Alignment for Large Language Models cites this paper.

FIRM: Federated In-client Regularized Multi-objective Alignment for Large Language Models Federated Communication-Efficient Multi-Objective Optimization

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-03T21:07:17.162042Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T21:07:17.162042Z digest=sha256:f595af4fc339b2ed45b79294c796c54a53dc6c7276a4657b2cebcee67c502d36