Paper Citation Record · LEDGER

Efficient Non-Parametric Uncertainty Quantification for Black-Box Large Language Models and Decision Planning

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2402.00251.

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

pith.paper-citation-record.v1
2402.00251 v1

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 2026-08-23T06:30:58.430688+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T20:37:55.140126Z

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

2
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 f6faee15-edb0-475f-bb63-186e2e39e3a5 · 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 Efficient Non-Parametric Uncertainty Quantification for Black-Box Large Language Models and Decision Planning

Reference 207

Resolution: unresolved; no resolver link, observed 2026-08-11T20:37:55.140126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a8452a20-fb53-4a6a-9828-386009bc9ecb · inbound

A Survey of Calibration Process for Black-Box LLMs cites this paper.

A Survey of Calibration Process for Black-Box LLMs Efficient Non-Parametric Uncertainty Quantification for Black-Box Large Language Models and Decision Planning

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T13:48:40.064221Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06cef772-bf41-4840-bd9e-8b4ed8dd5702 · 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 Efficient Non-Parametric Uncertainty Quantification for Black-Box Large Language Models and Decision Planning

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-22T23:22:15.477838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 08094221-0564-48d2-8d2a-4523de19ef6b · inbound

AGENT-X: Adaptive Guideline-based Expert Network for Threshold-free AI-generated teXt detection cites this paper.

AGENT-X: Adaptive Guideline-based Expert Network for Threshold-free AI-generated teXt detection Efficient Non-Parametric Uncertainty Quantification for Black-Box Large Language Models and Decision Planning

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T15:24:13.786679Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 156d37b8-995b-4701-830b-22a16b16dc63 · inbound

Speaking in Self-Assessing Tongues: On the Verbalized Confidence of LLMs in Machine Translation cites this paper.

Speaking in Self-Assessing Tongues: On the Verbalized Confidence of LLMs in Machine Translation Efficient Non-Parametric Uncertainty Quantification for Black-Box Large Language Models and Decision Planning

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-07-03T18:08:46.928447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.