Paper Citation Record · LEDGER

Reassessing How to Compare and Improve the Calibration of Machine Learning Models

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2406.04068.

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

pith.paper-citation-record.v1
2406.04068 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T21:03:04.001213Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T00:57:29.562967Z

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 e4416801-a843-458d-9aef-01e17c9abce0 · inbound

Rethinking Early Stopping: Refine, Then Calibrate cites this paper.

Rethinking Early Stopping: Refine, Then Calibrate Reassessing How to Compare and Improve the Calibration of Machine Learning Models

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-09T21:03:04.001213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 01d8107d-fee2-413a-855d-c1a6fa81203e · inbound

An Assessment of Human vs. Model Uncertainty in Soft-Label Learning and Calibration cites this paper.

An Assessment of Human vs. Model Uncertainty in Soft-Label Learning and Calibration Reassessing How to Compare and Improve the Calibration of Machine Learning Models

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-20T11:58:15.230435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 189c267b-7c96-45c9-975b-0d7f85a908be · inbound

MAAM: Anchor-Preserving Compression and Contextual Calibration for Chinese Discriminatory Language Detection cites this paper.

MAAM: Anchor-Preserving Compression and Contextual Calibration for Chinese Discriminatory Language Detection Reassessing How to Compare and Improve the Calibration of Machine Learning Models

Reference 46

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T00:57:29.564509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation caf1c7f9-6b4b-426a-97db-1c2d5627d3b3 · inbound

When Calibration Rankings Reverse: Accuracy-Controlled Evaluation for Fair Comparison of LLMs cites this paper.

When Calibration Rankings Reverse: Accuracy-Controlled Evaluation for Fair Comparison of LLMs Reassessing How to Compare and Improve the Calibration of Machine Learning Models

Reference 140

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T12:15:43.626171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.