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Paper Citation Record · LEDGER

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

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 17 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 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 17 of 17 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:12:44.483411Z

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

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-18T00:52:02.421389Z digest=sha256:59d0c6f89bb62506661deafc561a6c2d97bf7fd016b8c0cf8c8ccae5fed28122

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.

source=pdf_text observed=2026-08-07T15:12:44.483411Z digest=sha256:d440271973438d8c5c2df1bf28f40d5781eeb492fa63494f7af2e53face64267

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.

source=pdf_text observed=2026-08-07T11:56:44.972883Z digest=sha256:9a83d2f84f9746d541e7345985d8f430fc9b19e379ae2f512037f7b99989b438

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.

source=pdf_text observed=2026-08-07T05:38:25.085909Z digest=sha256:5cbdc470aa47b5fed61da68ec0faefb7edce9c4ead5cb2af0c667d008f0d7f69

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.

source=arxiv_source observed=2026-08-06T22:23:20.849354Z digest=sha256:5279d1379b9739a95de9afafcd4706f9e7546ab375345f4333fee9040a11f4df

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.

source=pdf_text observed=2026-08-04T17:41:04.988614Z digest=sha256:fbf836cba2c9bf754ed48fecb036d27a79809325278b6fe190dbdb5d6373f5e6

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.

source=arxiv_source observed=2026-08-03T10:48:02.975830Z digest=sha256:89df6fc71b7b791160077de02282d958af41499eee880bad3526857ffb381e51

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.

source=arxiv_source observed=2026-08-04T06:25:47.826683Z digest=sha256:80a1ec5bf8ededf7b6de1589e67f76de3433a010e03823bde0ed5ed1e2027b3e

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-10T19:41:00.530274Z digest=sha256:8eeaeddabe65e9375f34ee80eeb18c41117b079b9f29a06d55a558269e8d4944

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-10T06:36:55.334742Z digest=sha256:237607acf4db41eb993c2e03acbb52b97a44b350da858aaad07f6740a4cd494a

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-12T01:19:19.238980Z digest=sha256:21b6ab4c1546dd6d34c88c51f519a524fe844e511dc1459e3d8d9270e134a892

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-12T02:25:28.186490Z digest=sha256:00f4d608b2237f547c6cff42acc1fb49d6a6c163bd406dd7d4d43ef07e9006d2

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-12T02:15:53.024591Z digest=sha256:9cd9c5a8e69e360d2bbf6c218aa68b7efc553658fcaf5c000fb135d4b70a264b

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-29T13:23:01.482449Z digest=sha256:2a18b0af0ef82aeee8d5aeb07bd2e346e6135a16ee5957a7dc163b624c6fcf6b

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-26T16:24:25.357338Z digest=sha256:9db1aa17b4ee6c76a6ff4e817138471e1545d66063596c343a4e28f12520427f

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-25T23:52:07.754083Z digest=sha256:a19ab25b4433f91a6c9a1371d38f47247281fdccd9254bf5250215b8ed3ccd1e

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-07-01T02:17:19.540484Z digest=sha256:93989039a634e32922cc691d61aa1b0defa46fadbb35ca7e60416ccd5db28418