Paper Citation Record · LEDGER

A survey and taxonomy of loss functions in machine learning

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2301.05579.

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

pith.paper-citation-record.v1
2301.05579 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:16:58.840419Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T21:26:17.736977Z

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 dfcb92f0-c5e8-4599-8578-f2d089f029e3 · inbound

Neuro-Argumentative Learning with Case-Based Reasoning cites this paper.

Neuro-Argumentative Learning with Case-Based Reasoning A survey and taxonomy of loss functions in machine learning

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T15:16:58.840419Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ad7ba85e-afe2-4a90-93fb-a0426d1181f3 · inbound

Bulk-boundary decomposition of neural networks cites this paper.

Bulk-boundary decomposition of neural networks A survey and taxonomy of loss functions in machine learning

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-04T00:22:01.206440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7bdc0f8-e730-4d27-8676-3d4a4f157496 · inbound

Ratio-based Loss Functions cites this paper.

Ratio-based Loss Functions A survey and taxonomy of loss functions in machine learning

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:26:17.742167Z

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.

Observation ccb638f8-d95f-4e73-866e-a567ffbcde31 · inbound

A Unified Framework for In-Context Learning with Causal and Masked Language Models cites this paper.

A Unified Framework for In-Context Learning with Causal and Masked Language Models A survey and taxonomy of loss functions in machine learning

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-11T21:50:04.825590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1eed5e50-c827-4064-b938-f2032ff12e20 · inbound

Reconstruction of Primordial Power Spectrum from Gravitational Waves of High-Redshift Black Hole Binaries cites this paper.

Reconstruction of Primordial Power Spectrum from Gravitational Waves of High-Redshift Black Hole Binaries A survey and taxonomy of loss functions in machine learning

Reference 88

Resolution: unresolved; no resolver link, observed 2026-07-14T06:46:02.916338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.