Paper Citation Record · LEDGER

Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 21 inbound Pith citation observations for arXiv:2308.16175.

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

pith.paper-citation-record.v1
2308.16175 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 21 of 21 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 21 of 21 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:41:28.023049Z

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
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External citation measurements

7
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 79cba87f-e63c-4734-8c9c-acf692eb4753 · inbound

Semantic Entropy Probes: Robust and Cheap Hallucination Detection in LLMs cites this paper.

Semantic Entropy Probes: Robust and Cheap Hallucination Detection in LLMs Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-18T00:52:02.488292Z

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 c4bff900-1944-43c0-8c20-be16c4a8f053 · 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 Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-11T20:37:54.637570Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5cd983e3-b7af-431e-90b4-9b41f5fe38cc · inbound

UAlign: Leveraging Uncertainty Estimations for Factuality Alignment on Large Language Models cites this paper.

UAlign: Leveraging Uncertainty Estimations for Factuality Alignment on Large Language Models Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T14:40:29.232110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5d1f2bd-0fbf-40f6-a8a3-8a4240a5301c · inbound

Aligning Large Language Models for Faithful Integrity Against Opposing Argument cites this paper.

Aligning Large Language Models for Faithful Integrity Against Opposing Argument Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T22:35:43.841810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0f82ba5-7554-464e-b1ac-7c34b978dde1 · inbound

Language Models for Materials Discovery and Sustainability: Progress, Challenges, and Opportunities cites this paper.

Language Models for Materials Discovery and Sustainability: Progress, Challenges, and Opportunities Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness

Reference 167

Resolution: unresolved; no resolver link, observed 2026-08-16T11:41:28.023049Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2baae7d2-a69e-4f8c-9f47-883e52906b9e · inbound

Conformal Language Model Reasoning with Coherent Factuality cites this paper.

Conformal Language Model Reasoning with Coherent Factuality Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness

Reference 5399

Resolution: unresolved; no resolver link, observed 2026-08-07T15:12:44.483411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97b68809-8e63-4ee9-a807-ac261647c27f · inbound

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation cites this paper.

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T11:56:44.972883Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fea5095f-e75c-4a34-9ac4-a00738a9e10f · inbound

From Calibration to Collaboration: LLM Uncertainty Quantification Should Be More Human-Centered cites this paper.

From Calibration to Collaboration: LLM Uncertainty Quantification Should Be More Human-Centered Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T05:38:25.085909Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5002d273-af16-4be7-a6fd-afe7e633ac83 · inbound

The Consistency Hypothesis in Uncertainty Quantification for Large Language Models cites this paper.

The Consistency Hypothesis in Uncertainty Quantification for Large Language Models Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T22:23:20.849354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54682817-b1a9-48f9-a483-c90d461e4eb9 · inbound

HalluField: Detecting LLM Hallucinations via Field-Theoretic Modeling cites this paper.

HalluField: Detecting LLM Hallucinations via Field-Theoretic Modeling Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-04T17:41:04.988614Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9454b443-4920-4c54-91b7-81570c0f9b52 · inbound

Entropy Sentinel: Probing Entropy Traces for LLM Monitoring cites this paper.

Entropy Sentinel: Probing Entropy Traces for LLM Monitoring Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T10:48:02.975830Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d392598-ab96-4612-aa91-76496cb9c930 · inbound

Entropy Sentinel: Probing Entropy Traces for LLM Monitoring cites this paper.

Entropy Sentinel: Probing Entropy Traces for LLM Monitoring Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T06:25:47.826683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ffb5ef71-0cb9-4cf9-b117-de311ca5a92d · inbound

Towards Trustworthy Report Generation: A Deep Research Agent with Progressive Confidence Estimation and Calibration cites this paper.

Towards Trustworthy Report Generation: A Deep Research Agent with Progressive Confidence Estimation and Calibration Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-10T22:35:52.075373Z

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 fb741969-099c-4e3c-9567-c76ec7970e30 · inbound

Calibrating Model-Based Evaluation Metrics for Summarization cites this paper.

Calibrating Model-Based Evaluation Metrics for Summarization Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness

Reference 100

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T06:41:36.935226Z

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 9d92ca1c-ddd3-4a09-baf1-b9ff9910416f · inbound

Sanity Checks for Long-Form Hallucination Detection cites this paper.

Sanity Checks for Long-Form Hallucination Detection Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-12T08:06:28.266389Z

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 94ba2c47-4a49-4ebf-b417-0e9dc66cd748 · inbound

Optimality of Sub-network Laplace Approximations: New Results and Methods cites this paper.

Optimality of Sub-network Laplace Approximations: New Results and Methods Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness

Reference 12

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T07:37:16.237018Z

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 cf8aac03-2602-427a-80ae-bbc3ec12c8a6 · inbound

Fin-Bias: Comprehensive Evaluation for LLM Decision-Making under human bias in Finance Domain cites this paper.

Fin-Bias: Comprehensive Evaluation for LLM Decision-Making under human bias in Finance Domain Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness

Reference 74

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T02:16:15.737433Z

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 82c3387e-3936-4aa5-9287-0d46ae1998c7 · inbound

Functional Entropy: Predicting Functional Correctness in LLM-Generated Code with Uncertainty Quantification cites this paper.

Functional Entropy: Predicting Functional Correctness in LLM-Generated Code with Uncertainty Quantification Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-06-29T13:23:27.684095Z

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 32029c63-9af7-4281-9e7b-c9bcfb038dc6 · inbound

Qiskit Code Migration with LLMs cites this paper.

Qiskit Code Migration with LLMs Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness

Reference 146

Resolution: verified exact; arxiv_id, observed 2026-06-26T16:29:35.497257Z

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 8219bdcd-d35a-4190-8d6b-7a5fbeaf27d6 · inbound

Beyond Logprobs: A Multi-Signal Confidence Engine for LLM-Based Document Field Extraction cites this paper.

Beyond Logprobs: A Multi-Signal Confidence Engine for LLM-Based Document Field Extraction Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-07-04T17:09:59.423569Z

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 63cdc2fc-a663-411a-bd1a-47641439c54f · inbound

When Calibration Rankings Reverse: Accuracy-Controlled Evaluation for Fair Comparison of LLMs cites this paper.

When Calibration Rankings Reverse: Accuracy-Controlled Evaluation for Fair Comparison of LLMs Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness

Reference 60

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T12:15:43.718164Z

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.