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Paper Citation Record · LEDGER

Training verified learners with learned verifiers

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1805.10265.

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

pith.paper-citation-record.v1
1805.10265 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 2026-08-06T06:34:29.942622+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T08:39:32.435146Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T19:51:09.669384Z

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 0fbb1bb7-3a4d-4382-9b6f-3b21fd4bd7a8 · inbound

Learning to Optimize by Differentiable Programming cites this paper.

Learning to Optimize by Differentiable Programming Training verified learners with learned verifiers

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-03T08:39:32.435146Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T08:39:32.435146Z digest=sha256:fa89de2faa5bfdf0887ac73c2529b0432618d7002a6a8d96cb64934de5d8ea8c

Observation 0f2289cf-6b31-4db1-8f69-73476d784bef · inbound

Relaxation-Informed Training of Neural Network Surrogate Models cites this paper.

Relaxation-Informed Training of Neural Network Surrogate Models Training verified learners with learned verifiers

Reference 50

Resolution
verified exact
arxiv_id, observed 2026-07-04T22:48:22.632767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-08T10:56:03.732758Z digest=sha256:ae6fc3129bbb9d53d2448393baed1edeb2c6096e8694f061b9c87340630e26d1