Paper Citation Record · LEDGER

Are Large Language Models More Honest in Their Probabilistic or Verbalized Confidence?

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2408.09773.

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

pith.paper-citation-record.v1
2408.09773 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T04:42:00.343211Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

1
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 13792e9b-7ff1-48bd-8fda-5494bbdf0526 · inbound

Assessing GPT Model Uncertainty in Mathematical OCR Tasks via Entropy Analysis cites this paper.

Assessing GPT Model Uncertainty in Mathematical OCR Tasks via Entropy Analysis Are Large Language Models More Honest in Their Probabilistic or Verbalized Confidence?

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-12T04:42:00.343211Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 358e39c3-1000-42d3-9af8-5da06136ec42 · inbound

A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future Directions cites this paper.

A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future Directions Are Large Language Models More Honest in Their Probabilistic or Verbalized Confidence?

Reference 155

Resolution: unresolved; no resolver link, observed 2026-08-11T20:37:54.990736Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 75e18df9-c47d-42a1-bab0-bab40123489a · inbound

Influences on LLM Calibration: A Study of Response Agreement, Loss Functions, and Prompt Styles cites this paper.

Influences on LLM Calibration: A Study of Response Agreement, Loss Functions, and Prompt Styles Are Large Language Models More Honest in Their Probabilistic or Verbalized Confidence?

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-10T21:45:55.353869Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48b7ca60-1d8d-474b-8ad3-e35572399adc · inbound

Self-Reported Confidence of Large Language Models in Gastroenterology: Analysis of Commercial, Open-Source, and Quantized Models cites this paper.

Self-Reported Confidence of Large Language Models in Gastroenterology: Analysis of Commercial, Open-Source, and Quantized Models Are Large Language Models More Honest in Their Probabilistic or Verbalized Confidence?

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-22T23:22:15.471868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 328026c1-c9bb-47da-8d15-cff93c5a96f2 · inbound

Towards Harmonized Uncertainty Estimation for Large Language Models cites this paper.

Towards Harmonized Uncertainty Estimation for Large Language Models Are Large Language Models More Honest in Their Probabilistic or Verbalized Confidence?

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T14:25:22.456919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8763afe2-221f-4c48-aadb-0e5333fa5e5d · inbound

Beyond Semantic Equivalence: Logical Graphs for LLM Uncertainty Quantification cites this paper.

Beyond Semantic Equivalence: Logical Graphs for LLM Uncertainty Quantification Are Large Language Models More Honest in Their Probabilistic or Verbalized Confidence?

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-01T19:46:59.691249Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.