Paper Citation Record · LEDGER

A Survey of Calibration Process for Black-Box LLMs

As of 21 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 4 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 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T13:48:40.203898Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:07:50.703898Z

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

16 of 16 outbound references displayed

verified exact0
verified fuzzy1
unresolved15
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 732f59f5-ed1f-493c-be68-4ba243cc6f26 · outbound

This paper cites Look Before You Leap: An Exploratory Study of Uncertainty Measurement for Large Language Models.

A Survey of Calibration Process for Black-Box LLMs Look Before You Leap: An Exploratory Study of Uncertainty Measurement for Large Language Models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T13:48:40.023939Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b43b8860-4334-4052-83d1-732ea4af838f · outbound

This paper cites Measuring and Narrowing the Compositionality Gap in Language Models.

A Survey of Calibration Process for Black-Box LLMs Measuring and Narrowing the Compositionality Gap in Language Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T13:48:40.040446Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 704f4992-1364-40d0-b0e2-d2db983c04b8 · outbound

This paper cites Llamas Know What GPTs Don't Show: Surrogate Models for Confidence Estimation.

A Survey of Calibration Process for Black-Box LLMs Llamas Know What GPTs Don't Show: Surrogate Models for Confidence Estimation

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T13:48:40.045629Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

This paper cites Efficient Non-Parametric Uncertainty Quantification for Black-Box Large Language Models and Decision Planning.

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 af9711ed-856e-4e79-95df-f95c0051aa06 · outbound

This paper cites Black-box Uncertainty Quantification Method for LLM-as-a-Judge.

A Survey of Calibration Process for Black-Box LLMs Black-box Uncertainty Quantification Method for LLM-as-a-Judge

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T13:48:40.102166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94c56138-c5dd-433c-a4c6-02d5fee53782 · outbound

This paper cites SportQA: A Benchmark for Sports Understanding in Large Language Models.

A Survey of Calibration Process for Black-Box LLMs SportQA: A Benchmark for Sports Understanding in Large Language Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-11T13:48:40.153721Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ad742b99-18b2-451a-8b57-72f214ace831 · outbound

This paper cites ReAct: Synergizing Reasoning and Acting in Language Models.

A Survey of Calibration Process for Black-Box LLMs ReAct: Synergizing Reasoning and Acting in Language Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T13:48:40.194494Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2abe96e0-62f0-4858-800f-2b43bc8b4d7f · outbound

This paper cites These methods focus on evaluating the model’s ability to distinguish be- tween correct and incorrect samples at various con- fidence thresholds, but their emphases differ.

A Survey of Calibration Process for Black-Box LLMs These methods focus on evaluating the model’s ability to distinguish be- tween correct and incorrect samples at various con- fidence thresholds, but their emphases differ

Reference 2013

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T13:48:40.462209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ba213b30-62b1-47c8-8754-13b7ab796a3f · outbound

This paper cites Question Answering with Subgraph Embeddings.

A Survey of Calibration Process for Black-Box LLMs Question Answering with Subgraph Embeddings

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-11T13:48:39.920994Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d1251da6-f93d-48bb-9f3a-75f39e95207d · outbound

This paper cites an unresolved cited work.

A Survey of Calibration Process for Black-Box LLMs Unresolved cited work

Reference 2015

Resolution: unresolved; raw_fallback, observed 2026-08-11T13:48:40.477980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c88a1d24-2d47-420f-a6f4-a33fdb98c01d · outbound

This paper cites Top-label calibration and multiclass-to-binary reductions.

A Survey of Calibration Process for Black-Box LLMs Top-label calibration and multiclass-to-binary reductions

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-11T13:48:39.983849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e79c679-6252-4007-96b3-896084d0b399 · outbound

This paper cites Measuring Massive Multitask Language Understanding.

A Survey of Calibration Process for Black-Box LLMs Measuring Massive Multitask Language Understanding

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-11T13:48:40.018003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31846bd5-639a-4355-9207-fa2e20d5919f · outbound

This paper cites Are NLP Models really able to Solve Simple Math Word Problems?.

A Survey of Calibration Process for Black-Box LLMs Are NLP Models really able to Solve Simple Math Word Problems?

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-11T13:48:40.035299Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea7834fc-af23-46bc-bf46-ef753cc43ee5 · outbound

This paper cites GPT-4 Technical Report.

A Survey of Calibration Process for Black-Box LLMs GPT-4 Technical Report

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-11T13:48:39.915295Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb2067a2-c4fa-4293-a719-a719a50d6748 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

A Survey of Calibration Process for Black-Box LLMs Training Verifiers to Solve Math Word Problems

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-11T13:48:39.944316Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b9a627a3-3e13-4009-a66a-7b327cdc1032 · outbound

This paper cites When Do LLMs Need Retrieval Augmentation? Mitigating LLMs' Overconfidence Helps Retrieval Augmentation.

A Survey of Calibration Process for Black-Box LLMs When Do LLMs Need Retrieval Augmentation? Mitigating LLMs' Overconfidence Helps Retrieval Augmentation

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-11T13:48:40.030345Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 9b275fda-3be1-4b5d-9c6c-a4a8f2794bfa · inbound

Maximizing Confidence Alone Improves Reasoning cites this paper.

Maximizing Confidence Alone Improves Reasoning A Survey of Calibration Process for Black-Box LLMs

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-07T13:07:50.703898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3f2b8bbc-d76e-4bfe-9f49-2352929d9909 · inbound

Understanding How University Guidelines Address Privacy and Security Issues of Generative AI in Academic Settings cites this paper.

Understanding How University Guidelines Address Privacy and Security Issues of Generative AI in Academic Settings A Survey of Calibration Process for Black-Box LLMs

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-06T22:50:01.001810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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 2026-08-21T06:32:19.484+00:00.

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.