Paper Citation Record · LEDGER

Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents

As of 19 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 7 inbound Pith citation observations for arXiv:2505.22655.

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

pith.paper-citation-record.v1
2505.22655 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:08:20.006535Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T22:09:05.655499Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T04:27:36.370794Z

Reference resolution

24 of 24 outbound references displayed

verified exact4
verified fuzzy2
unresolved18
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3c30939c-192d-4370-84e2-8e42ba9238bb · outbound

This paper cites A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity.

Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T13:08:17.956464Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f40498b4-636f-421f-b8c5-733a2c019fb7 · outbound

This paper cites How disentangled are your classifi- cation uncertainties?arXiv preprint arXiv:2408.12175,.

Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents How disentangled are your classifi- cation uncertainties?arXiv preprint arXiv:2408.12175,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T13:08:18.476898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a519f61-d99c-4f7c-86f0-02bc0d75c1a2 · outbound

This paper cites Ensembling over Classifiers: a Bias-Variance Perspective.

Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents Ensembling over Classifiers: a Bias-Variance Perspective

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:08:21.178445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 59439465-68dc-4368-b170-1cfd2ac423ce · outbound

This paper cites Large Language Models Must Be Taught to Know What They Don't Know.

Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents Large Language Models Must Be Taught to Know What They Don't Know

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T13:08:18.941111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62acad5f-f6e3-47d7-8ece-f7061b80ab60 · outbound

This paper cites Accessed on 04.08.2024.

Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents Accessed on 04.08.2024

Reference 13

Resolution: verified exact; raw_fallback, observed 2026-08-07T13:08:20.764011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2129dd59-5957-4438-8cee-7371585d7885 · outbound

This paper cites From Risk to Uncertainty: Generating Predictive Uncertainty Measures via Bayesian Estimation.

Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents From Risk to Uncertainty: Generating Predictive Uncertainty Measures via Bayesian Estimation

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T13:08:19.166517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d24a72a7-b55d-4551-8283-cd239e7401e6 · outbound

This paper cites AmbigQA: Answering ambiguous open- domain questions.

Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents AmbigQA: Answering ambiguous open- domain questions

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:08:22.046194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 47c5f2b5-7efa-49bf-a1df-15a4d871ae55 · outbound

This paper cites On Uncertainty In Natural Language Processing.

Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents On Uncertainty In Natural Language Processing

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T13:08:19.661974Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 295cd4d6-2235-4904-b95c-1f4ed67d338b · outbound

This paper cites SaySelf: Teaching LLMs to Express Confidence with Self-Reflective Rationales.

Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents SaySelf: Teaching LLMs to Express Confidence with Self-Reflective Rationales

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T13:08:19.736992Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47cf881e-f404-4abb-af3b-01288acd1636 · outbound

This paper cites Gal Yona, Roee Aharoni, and Mor Geva.

Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents Gal Yona, Roee Aharoni, and Mor Geva

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T13:08:19.826677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48bcb10c-83f2-41a5-b16b-5e945c44b410 · outbound

This paper cites Boxuan Zhang and Ruqi Zhang.

Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents Boxuan Zhang and Ruqi Zhang

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T13:08:19.913915Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65bc28ba-f6f4-49ae-a915-9903071d539e · outbound

This paper cites CoT-UQ: Improving Response-wise Uncertainty Quantification in LLMs with Chain-of-Thought.

Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents CoT-UQ: Improving Response-wise Uncertainty Quantification in LLMs with Chain-of-Thought

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T13:08:20.006535Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 902e44a9-05b4-4465-af69-1bb6ce4a38df · outbound

This paper cites Uncertainty in Natural Language Generation: From Theory to Applications.

Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents Uncertainty in Natural Language Generation: From Theory to Applications

Reference 1990

Resolution: unresolved; no resolver link, observed 2026-08-07T13:08:17.822126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40504043-21bc-49ed-a9f5-2530d912f58d · outbound

This paper cites Bayesian Active Learning for Classification and Preference Learning.

Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents Bayesian Active Learning for Classification and Preference Learning

Reference 1997

Resolution: unresolved; no resolver link, observed 2026-08-07T13:08:18.790591Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08b89daa-dd33-4aaf-9d60-647456694234 · outbound

This paper cites Towards Clear Expectations for Uncertainty Estimation.

Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents Towards Clear Expectations for Uncertainty Estimation

Reference 2004

Resolution: unresolved; no resolver link, observed 2026-08-07T13:08:18.341728Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b762aa4c-4620-4d6d-a604-719f114f426b · outbound

This paper cites Know What You Don't Know: Unanswerable Questions for SQuAD.

Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents Know What You Don't Know: Unanswerable Questions for SQuAD

Reference 2013

Resolution: unresolved; no resolver link, observed 2026-08-07T13:08:19.499743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 86f3acbf-2bf7-4995-a71e-576f024cd856 · outbound

This paper cites Sources of Uncertainty in Supervised Machine Learning -- A Statisticians' View.

Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents Sources of Uncertainty in Supervised Machine Learning -- A Statisticians' View

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-07T13:08:18.565726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aebffad1-5729-49d3-b390-d579d55508ea · outbound

This paper cites On Information-Theoretic Measures of Predictive Uncertainty.

Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents On Information-Theoretic Measures of Predictive Uncertainty

Reference 2018

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:08:20.340252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5a315e8c-e0d1-4fed-ab43-5d818c83ef4d · outbound

This paper cites Perceptions of Linguistic Uncertainty by Language Models and Humans.

Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents Perceptions of Linguistic Uncertainty by Language Models and Humans

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-07T13:08:18.215676Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 71c7f462-0115-4ce0-bacd-121c915d0c26 · outbound

This paper cites Teaching Models to Express Their Uncertainty in Words.

Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents Teaching Models to Express Their Uncertainty in Words

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-07T13:08:19.342106Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a65b683-5503-4cb0-97e6-78c8233bc268 · outbound

This paper cites DEUP: Direct Epistemic Uncertainty Prediction.

Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents DEUP: Direct Epistemic Uncertainty Prediction

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-07T13:08:19.269044Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 552126d3-345a-4bb0-bb04-3c6ebfbee4c6 · outbound

This paper cites Phiseg: Capturing uncertainty in medical image segmentation.

Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents Phiseg: Capturing uncertainty in medical image segmentation

Reference 2023

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:08:22.751517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 727a4147-c8c0-4a90-9af5-32285b8553d8 · outbound

This paper cites LLMs Will Always Hallucinate, and We Need to Live With This.

Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents LLMs Will Always Hallucinate, and We Need to Live With This

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T13:08:17.886108Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc7b383b-978e-4201-b74e-7319ec2c25b8 · outbound

This paper cites Andreas Kirsch.

Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents Andreas Kirsch

Reference 2025

Resolution: verified exact; raw_fallback, observed 2026-08-07T13:08:21.015355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

Observation 1157a48e-4657-443a-8ed3-1fa77b170a77 · inbound

Uncertainty Quantification on Graph Learning: A Survey cites this paper.

Uncertainty Quantification on Graph Learning: A Survey Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-05-24T02:28:46.095092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3c283511-0872-4d0b-b7f7-47baecbb0d76 · inbound

TokUR: Token-Level Uncertainty Estimation for Large Language Model Reasoning cites this paper.

TokUR: Token-Level Uncertainty Estimation for Large Language Model Reasoning Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-22T14:01:38.240097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 855dd36a-81e8-45c9-ac1e-e25c9e94aea7 · inbound

Uncertainty-Driven Reliability: Selective Prediction and Trustworthy Deployment in Modern Machine Learning cites this paper.

Uncertainty-Driven Reliability: Selective Prediction and Trustworthy Deployment in Modern Machine Learning Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-05T22:09:05.655499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b7ed1c1-00ed-47d0-9527-48323a230d0d · inbound

Proper Scoring Rules for Agentic Uncertainty Quantification cites this paper.

Proper Scoring Rules for Agentic Uncertainty Quantification Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-06-30T13:04:40.129284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e29d623c-56a5-4f74-9eb4-b7c468785b28 · inbound

Helicase: Uncertainty-Guided Supply Chain Knowledge Graph Construction with Autonomous Multi-Agent LLMs cites this paper.

Helicase: Uncertainty-Guided Supply Chain Knowledge Graph Construction with Autonomous Multi-Agent LLMs Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-06-29T17:23:44.604600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c40daffc-295c-4fa7-a03a-3f8b148a8877 · inbound

Can we trust our models? Epistemic calibration in second-order classification cites this paper.

Can we trust our models? Epistemic calibration in second-order classification Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-07-03T04:27:36.372448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 341f2f35-84e5-4268-9b26-e94c1319b1ba · inbound

Agentic Abstention: Do Agents Know When to Stop Instead of Act? cites this paper.

Agentic Abstention: Do Agents Know When to Stop Instead of Act? Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-06-30T09:54:34.361660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.