Paper Citation Record · LEDGER

Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2311.08718.

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

pith.paper-citation-record.v1
2311.08718 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:08:24.732075Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T10:35:42.049914Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation d9a4bc37-728d-4aa5-829c-dad13dc2ae8c · 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 Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-11T20:37:54.770696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57de3e07-26ba-4f57-a25a-25a7805226c6 · 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 Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-11T11:15:12.797618Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27ce2e2d-2ffa-493e-8e87-423a98958895 · inbound

Exploring the Potential for Large Language Models to Demonstrate Rational Probabilistic Beliefs cites this paper.

Exploring the Potential for Large Language Models to Demonstrate Rational Probabilistic Beliefs Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-16T12:08:24.732075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f58b672c-9994-404d-8fa5-8e05ec2023c7 · inbound

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

TokUR: Token-Level Uncertainty Estimation for Large Language Model Reasoning Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-22T14:01:38.464971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation b6ca4db4-f394-4934-9715-5f836f9c251e · inbound

Maximizing Confidence Alone Improves Reasoning cites this paper.

Maximizing Confidence Alone Improves Reasoning Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T13:07:47.723716Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4853dc53-6b14-4810-be50-d4e00f63bd33 · 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 Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T11:56:45.030255Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5053c3e0-ba61-48be-85fc-6ddb036efb9a · inbound

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

Calibrating Model-Based Evaluation Metrics for Summarization Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling

Reference 98

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T06:41:36.922937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 79cf7f0c-b3ff-4c84-afd5-362db999e4e9 · inbound

Can LLMs Use Linguistic Uncertainty Markers to Reliably Reflect Intrinsic Confidence? cites this paper.

Can LLMs Use Linguistic Uncertainty Markers to Reliably Reflect Intrinsic Confidence? Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-06-29T12:23:24.364015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 00725d78-404f-4e43-a659-1bf65259d50c · inbound

Reinforcement Learning with Metacognitive Feedback Elicits Faithful Uncertainty Expression in LLMs cites this paper.

Reinforcement Learning with Metacognitive Feedback Elicits Faithful Uncertainty Expression in LLMs Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-07-01T10:35:42.051519Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f515952c-fa96-4a95-ac26-2bd3818b4f7a · inbound

U-Lens: Supporting User Uncertainty Management in Long-Form LLM Responses cites this paper.

U-Lens: Supporting User Uncertainty Management in Long-Form LLM Responses Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling

Reference 44

Resolution: unresolved; no resolver link, observed 2026-07-14T10:32:54.448282Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.