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Paper Citation Record · LEDGER

KKT-based optimality conditions for neural network approximation

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2506.17305.

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

pith.paper-citation-record.v1
2506.17305 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 1 of 1 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T17:36:33.188434Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T23:57:28.948965Z

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 9980f652-239a-4a52-9fb6-df8f1d5ee96e · inbound

LEAF: A Learning-Enabled ADMM Framework for Accelerated Convex Optimization cites this paper.

LEAF: A Learning-Enabled ADMM Framework for Accelerated Convex Optimization KKT-based optimality conditions for neural network approximation

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-07-02T23:57:28.950404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-27T17:36:33.188434Z digest=sha256:6c0ba595c208b45b48a6784a910246922a39305b1c172d4274fe40a01ae54d5a