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Paper Citation Record · LEDGER

Uncertainty in Natural Language Generation: From Theory to Applications

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 16 inbound Pith citation observations for arXiv:2307.15703.

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

pith.paper-citation-record.v1
2307.15703 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 16 of 16 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:09:30.931487Z

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 35ee8a27-a328-4445-afde-fff8cef09f52 · inbound

Unconditional Truthfulness: Learning Unconditional Uncertainty of Large Language Models cites this paper.

Unconditional Truthfulness: Learning Unconditional Uncertainty of Large Language Models Uncertainty in Natural Language Generation: From Theory to Applications

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-23T22:13:30.075256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-23T22:12:30.050438Z digest=sha256:d56adb4506df3c2354e65432ea86d8c062259eacc7316980b85c7e4ea1d50573

Observation 04939746-65d6-4d03-ac75-36e09b076154 · inbound

Text-to-SQL Calibration: No Need to Ask -- Just Rescale Model Probabilities cites this paper.

Text-to-SQL Calibration: No Need to Ask -- Just Rescale Model Probabilities Uncertainty in Natural Language Generation: From Theory to Applications

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-12T14:09:41.139601Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T14:09:41.139601Z digest=sha256:489e5ceae8289c2e21d28ecef7a0b0b20fecf1ffa5bca3c84c5f8f683d483610

Observation 129e5070-2ebe-4445-b59c-48166829ac73 · inbound

Unanswerability Evaluation for Retrieval Augmented Generation cites this paper.

Unanswerability Evaluation for Retrieval Augmented Generation Uncertainty in Natural Language Generation: From Theory to Applications

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-11T14:17:45.445655Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:17:45.445655Z digest=sha256:cc8505783c18f6b94e93198a7fae927406040a4363c98665142134fa931dfed9

Observation 6e45831b-5342-4225-bd26-cbc47a380bde · inbound

Variability Need Not Imply Error: The Case of Adequate but Semantically Distinct Responses cites this paper.

Variability Need Not Imply Error: The Case of Adequate but Semantically Distinct Responses Uncertainty in Natural Language Generation: From Theory to Applications

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-11T11:15:12.650348Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T11:15:12.650348Z digest=sha256:45b6830bfeeb28acbbf75620ae06d714f5f1c81ccefd954a0b1d2e9ad14eaf0e

Observation f4ace10f-3980-45af-9bb5-c1fcdf6bfea3 · inbound

Token-Level Density-Based Uncertainty Quantification Methods for Eliciting Truthfulness of Large Language Models cites this paper.

Token-Level Density-Based Uncertainty Quantification Methods for Eliciting Truthfulness of Large Language Models Uncertainty in Natural Language Generation: From Theory to Applications

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-23T02:52:26.382148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-23T02:51:16.495409Z digest=sha256:33b17319318229b543a158add1c93ab6b8ac055f2c8b783c81210e7f946f61bd

Observation 6453ee10-ffea-4d1c-9209-0f6647b226b3 · inbound

Revisiting Uncertainty Quantification Evaluation in Language Models: Spurious Interactions with Response Length Bias Results cites this paper.

Revisiting Uncertainty Quantification Evaluation in Language Models: Spurious Interactions with Response Length Bias Results Uncertainty in Natural Language Generation: From Theory to Applications

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-16T12:09:30.931487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:09:30.931487Z digest=sha256:df38bf19165f45dd957f68c73bcd83dea17129535fc0ce8c79fdc824a593a644

Observation 761893b9-f75a-4d0d-a458-7ec9b272e09b · inbound

A Head to Predict and a Head to Question: Pre-trained Uncertainty Quantification Heads for Hallucination Detection in LLM Outputs cites this paper.

A Head to Predict and a Head to Question: Pre-trained Uncertainty Quantification Heads for Hallucination Detection in LLM Outputs Uncertainty in Natural Language Generation: From Theory to Applications

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-15T22:04:26.663137Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:04:26.663137Z digest=sha256:99d4364c2aafc66b49b06a334efd69ae2c6f89d7db85e225713506d92be3c379

Observation e322adc0-90e4-4824-a0c7-7065f991d9e5 · inbound

Efficient Hallucination Detection for LLMs Using Uncertainty-Aware Attention Heads cites this paper.

Efficient Hallucination Detection for LLMs Using Uncertainty-Aware Attention Heads Uncertainty in Natural Language Generation: From Theory to Applications

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-07T14:07:43.566451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:07:43.566451Z digest=sha256:ec0c91751b6a178aa833be79faf056a020136b341142b45acd7dcea6615890dd

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

Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents cites this paper.

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.

source=pdf_text observed=2026-08-07T13:08:17.822126Z digest=sha256:a73df9868881962df21a5cb7844f40678642b111b4139d2364d5ab1ff8f2b29a

Observation ffa29d2d-38a2-4878-8e7e-764e3c6dddee · inbound

Large Language Models Can Be a Viable Substitute for Expert Political Surveys When a Shock Disrupts Traditional Measurement Approaches cites this paper.

Large Language Models Can Be a Viable Substitute for Expert Political Surveys When a Shock Disrupts Traditional Measurement Approaches Uncertainty in Natural Language Generation: From Theory to Applications

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T05:59:43.841041Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:59:43.841041Z digest=sha256:769da0d0ee0aeb72382e7772d9a3a3d93d74320c950e3a2880eea60ee176f66c

Observation 22659387-9d50-4f37-a01d-edeaa016e923 · inbound

Gradients with Respect to Semantics Preserving Embeddings Tell the Uncertainty of Large Language Models cites this paper.

Gradients with Respect to Semantics Preserving Embeddings Tell the Uncertainty of Large Language Models Uncertainty in Natural Language Generation: From Theory to Applications

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-08T20:19:07.570337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-08T16:24:23.603760Z digest=sha256:19d32f9e661ef6ab42af438aae4d95e0634a82dc9247cf4b430f6d2a5797840b

Observation 43c22958-7ee0-4909-992a-2d5bb042fec6 · inbound

The Yes-Man Syndrome: Benchmarking Abstention in Embodied Robotic Agents cites this paper.

The Yes-Man Syndrome: Benchmarking Abstention in Embodied Robotic Agents Uncertainty in Natural Language Generation: From Theory to Applications

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-21T06:39:43.830061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-21T06:35:35.189340Z digest=sha256:068944259d9ff02141779ae85ba5d74d253db7b8a5d9a91b4040cc84c8995b58

Observation 21a9cf5a-97ff-46bf-be3a-1107ed5f07d1 · inbound

Clarify, Abstain or Answer? Strategising in Conversation with Belief-Augmented Generation cites this paper.

Clarify, Abstain or Answer? Strategising in Conversation with Belief-Augmented Generation Uncertainty in Natural Language Generation: From Theory to Applications

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-06-29T21:23:58.711228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-06-29T21:23:34.624527Z digest=sha256:40f692afe3611278e97456025a2e4167430a2db0782a72c2fa54c9c904b2a584

Observation 9ad8c05c-b7eb-41d3-9cfa-b4b85bef5d66 · inbound

Epistemic Uncertainty Is Not the Reducible Kind cites this paper.

Epistemic Uncertainty Is Not the Reducible Kind Uncertainty in Natural Language Generation: From Theory to Applications

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-06-27T07:50:43.170645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-06-27T07:50:01.856954Z digest=sha256:6bdbea6750f318cf76040c408794cf30c23ce9fdb8e6313765dd8759cf338eb4

Observation ef1ae80f-81b7-4fd1-9948-83a10c9229cf · inbound

Uncertainty Decomposition for Clarification Seeking in LLM Agents cites this paper.

Uncertainty Decomposition for Clarification Seeking in LLM Agents Uncertainty in Natural Language Generation: From Theory to Applications

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-07-04T00:59:21.383248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-26T20:44:06.027685Z digest=sha256:febbd39314a91bd712d46746bf4a00b3f235ba4dec083c4274689557c000b62d

Observation b8cbafa2-8074-44ed-8f6a-b9f459988fe4 · 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 Uncertainty in Natural Language Generation: From Theory to Applications

Reference 12

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T12:15:43.650225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-01T02:17:19.540484Z digest=sha256:f744a4e921149294bb90390d13b9d4a979584eb0116a8fb7a5d77ff0a7c1709e