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Paper Citation Record · LEDGER

Loss Functions and Metrics in Deep Learning

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2307.02694.

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

pith.paper-citation-record.v1
2307.02694 v5

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 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:32:53.432291Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T23:41:16.977190Z

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 6e83b4c8-5af9-4201-9939-05fa456612a6 · inbound

The Courage to Stop: Overcoming Sunk Cost Fallacy in Deep Reinforcement Learning cites this paper.

The Courage to Stop: Overcoming Sunk Cost Fallacy in Deep Reinforcement Learning Loss Functions and Metrics in Deep Learning

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-07T00:32:53.432291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T00:32:53.432291Z digest=sha256:94daaec3bf2acd5db43a5f7453b53e3fee1f2f054b7c1d6bc1a328e89aeda0e9

Observation ea4a9e71-fbf1-4b2d-89ea-4096c634edcc · inbound

A Comprehensive Analysis of Accuracy and Robustness in Quantum Neural Networks cites this paper.

A Comprehensive Analysis of Accuracy and Robustness in Quantum Neural Networks Loss Functions and Metrics in Deep Learning

Reference 41

Resolution
verified exact
arxiv_id, observed 2026-05-11T23:41:16.979751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-07T16:29:39.158645Z digest=sha256:962294777b62d533ff886af86379178a4b2b12c94ffc64dc1cbd1497a46552ee