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Paper Citation Record · LEDGER

A Survey of Calibration Process for Black-Box LLMs

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2412.12767.

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

pith.paper-citation-record.v1
2412.12767 v1

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 2026-08-04T20:42:51.961770Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T03:39:30.629875Z

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 3664f820-0d29-43c4-8012-1c2c4b106734 · inbound

A Systematic Evaluation of Black-Box Uncertainty Estimation Methods for Large Language Models cites this paper.

A Systematic Evaluation of Black-Box Uncertainty Estimation Methods for Large Language Models A Survey of Calibration Process for Black-Box LLMs

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-07-04T03:39:30.631972Z

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=2026-06-26T17:46:00.822375Z digest=sha256:b5328f4786c229806045fb821386d5f4aac32fc334f9b2f9ed1c43875cf84204

Observation ea20bbbc-c0f3-4d6d-9b09-4d913f21f0f0 · inbound

Can You Trust the Confidence? ConfBench for Vision-Language Models on Document Extraction cites this paper.

Can You Trust the Confidence? ConfBench for Vision-Language Models on Document Extraction A Survey of Calibration Process for Black-Box LLMs

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-04T20:42:51.961770Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T20:42:51.961770Z digest=sha256:7318e4fa5348c9a2daea2cb4001797ccb4d8ca46e1f552ec8a6a7b1c3a8de4a0