Paper Citation Record · LEDGER

A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future Directions

As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2412.05563.

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

pith.paper-citation-record.v1
2412.05563 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 2026-08-04T06:34:03.388597+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T09:15:22.146386Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-10T06:15:00.866473Z

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 68c6dc13-b437-4209-88f2-01c45415c096 · inbound

LLM-Powered AI Agent Systems and Their Applications in Industry cites this paper.

LLM-Powered AI Agent Systems and Their Applications in Industry A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future Directions

Reference 99

Resolution: verified exact; arxiv_id, observed 2026-05-22T14:06:37.977969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 28daabab-5e04-4fa2-bea7-63e49f2de664 · inbound

Measuring and mitigating overreliance to build human-compatible AI cites this paper.

Measuring and mitigating overreliance to build human-compatible AI A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future Directions

Reference 108

Resolution: verified exact; arxiv_id, observed 2026-05-21T22:40:43.440871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 40c2a397-64ab-4dca-8fdc-a88a4630b6e5 · inbound

Check Yourself Before You Wreck Yourself: Selectively Quitting Improves LLM Agent Safety cites this paper.

Check Yourself Before You Wreck Yourself: Selectively Quitting Improves LLM Agent Safety A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future Directions

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-04T09:15:22.146386Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63cae89f-0b9b-4e46-a40c-df5ce0a955c4 · inbound

Complementing Self-Consistency with Cross-Model Disagreement for Uncertainty Quantification cites this paper.

Complementing Self-Consistency with Cross-Model Disagreement for Uncertainty Quantification A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future Directions

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-10T06:31:30.571184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 1ce7c9c4-499c-4b01-861c-74ae3bd97f5d · inbound

How Language Models Process Out-of-Distribution Inputs: A Two-Pathway Framework cites this paper.

How Language Models Process Out-of-Distribution Inputs: A Two-Pathway Framework A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future Directions

Reference 21

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T15:31:20.945486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 324327d3-1722-4a2a-9416-06b3f95e7492 · inbound

Zero-Shot Confidence Estimation for Small LLMs: When Supervised Baselines Aren't Worth Training cites this paper.

Zero-Shot Confidence Estimation for Small LLMs: When Supervised Baselines Aren't Worth Training A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future Directions

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:31:07.299146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 83cdd044-5dc8-4efb-82b1-01366504d43b · 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 A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future Directions

Reference 8

Resolution: metadata mismatch; arxiv_id, observed 2026-05-08T20:19:07.590953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b5541132-8ba6-41bc-9ce6-539d813973ce · inbound

Breaking the Chains of Probability: Neutrosophic Logic as a New Framework for Epistemic Uncertainty in Large Language Models cites this paper.

Breaking the Chains of Probability: Neutrosophic Logic as a New Framework for Epistemic Uncertainty in Large Language Models A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future Directions

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-06-30T16:35:12.251597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 072f379e-0fee-4c6b-b28a-2f0133e56076 · 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 A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future Directions

Reference 22

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T13:23:27.721661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 11879a95-9cb3-4e33-95d4-ee20649dae65 · inbound

DECK: A Consistency x Confidence Taxonomy of LLM Hallucinations cites this paper.

DECK: A Consistency x Confidence Taxonomy of LLM Hallucinations A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future Directions

Reference 41

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T22:56:19.761102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.