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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 2026-08-09T06:31:02.800959+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
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  • 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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T00:52:02.421389Z digest=sha256:33d04307cc4bf3e81de7fc879e969f1ddf6eafaba427886f23f08c08f3b22a49

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:af4879a892bdc496873978b65e20493382ae51ba5d2bce0b9dbcd36e71a645a8

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=sha256:06e6c26b15ee8f482ba4189e2bd60cefcea7589c3b42fe894e4336dfa866b727

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=sha256:81385223f2ed00541b68d4e927de500388b638650fe155fd407c4534bf79e5c5

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-10T19:41:00.530274Z digest=sha256:028221588856519f3f98da08ac405a85dda0cb1849cc2501c95258d505688bc9

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-10T06:36:55.334742Z digest=sha256:99048aa0d6f548a9270e6aa2c2dbdcfb810309d18dfd3acd92b02f32d55fdd13

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-12T01:19:19.238980Z digest=sha256:478e7d62cef40969e4f6e8b5be8aba826ef90dd95e4d903f6ebafa75e9439c50

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-12T02:25:28.186490Z digest=sha256:4899c36a1940f94f706b46e78ce261ed5869af8f42f5bdde1c0f89c598821a17

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-12T02:15:53.024591Z digest=sha256:9b1aa00c9efbbc3a9e75540299c7026c1c202f66f671597b10b466d27b1a8376

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-29T13:23:01.482449Z digest=sha256:d6b5ad13ad7983addb70c7069ecb854cb943f6150dbed4a45578d30b98986511

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-26T16:24:25.357338Z digest=sha256:046d9e4ae28ed62dcbd2f97b23fa5deb59cdd7328ac71b9374e4cfd9b7d51069

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-25T23:52:07.754083Z digest=sha256:f0512a15e8fd2139d3a241f0e0ed4743c5d7f20e74d95fe58fb94d2615c732f7

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 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-07-01T02:17:19.540484Z digest=sha256:f5126ed4e76ca7d0ce38484f8693672200fb24950cfc7972b0161497bb114a06