Paper Citation Record · LEDGER

The challenge of uncertainty quantification of large language models in medicine

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2504.05278.

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

pith.paper-citation-record.v1
2504.05278 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:44:15.178000Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-10T18:57:31.628006Z

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 ddd012bd-f656-4762-ba50-88888c623c80 · inbound

Evaluating Prompt Engineering Techniques for Accuracy and Confidence Elicitation in Medical LLMs cites this paper.

Evaluating Prompt Engineering Techniques for Accuracy and Confidence Elicitation in Medical LLMs The challenge of uncertainty quantification of large language models in medicine

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T12:44:15.178000Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea7c5c1b-9d02-4b88-a817-e64f8e5a4641 · inbound

Rethinking Testing for LLM Applications: Characteristics, Challenges, and a Lightweight Interaction Protocol cites this paper.

Rethinking Testing for LLM Applications: Characteristics, Challenges, and a Lightweight Interaction Protocol The challenge of uncertainty quantification of large language models in medicine

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-05T14:55:56.599407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 33651c28-aa52-4aba-8efc-d1a9bc3022a2 · inbound

Rule-Based Moral Principles for Explaining Uncertainty in Natural Language Generation cites this paper.

Rule-Based Moral Principles for Explaining Uncertainty in Natural Language Generation The challenge of uncertainty quantification of large language models in medicine

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-04T22:45:42.550373Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 539c49ca-cd90-44d1-8f6c-4a7e0d4b0d71 · inbound

Generative Artificial Intelligence in Bioinformatics: A Systematic Review of Models, Applications, and Methodological Advances cites this paper.

Generative Artificial Intelligence in Bioinformatics: A Systematic Review of Models, Applications, and Methodological Advances The challenge of uncertainty quantification of large language models in medicine

Reference 145

Resolution: unresolved; no resolver link, observed 2026-08-04T00:00:09.669918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c5421787-3fb7-41d6-81d0-dda8346e42d1 · inbound

LEC: Linear Expectation Constraints for Selection-Conditioned Risk Control in Selective Prediction and Routing Systems cites this paper.

LEC: Linear Expectation Constraints for Selection-Conditioned Risk Control in Selective Prediction and Routing Systems The challenge of uncertainty quantification of large language models in medicine

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-03T19:18:18.058963Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67c13e4b-5cf4-4b47-a448-bbb0ea9c08d0 · inbound

MedGuards: Multi-Agent System for Reliable Medical Error Detection and Correction cites this paper.

MedGuards: Multi-Agent System for Reliable Medical Error Detection and Correction The challenge of uncertainty quantification of large language models in medicine

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-07-04T20:00:08.335934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 173e64c4-691a-4401-8c22-a62b4dc3463e · inbound

MedGuards: Multi-Agent System for Reliable Medical Error Detection and Correction cites this paper.

MedGuards: Multi-Agent System for Reliable Medical Error Detection and Correction The challenge of uncertainty quantification of large language models in medicine

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-06-29T18:33:51.175825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d9afada4-5b1c-4fa2-8f99-e842f8179909 · inbound

Aligning Clinical Needs and AI Capabilities: A Survey on LLMs for Medical Reasoning cites this paper.

Aligning Clinical Needs and AI Capabilities: A Survey on LLMs for Medical Reasoning The challenge of uncertainty quantification of large language models in medicine

Reference 200

Resolution: metadata mismatch; local_arxiv, observed 2026-07-10T18:57:31.629473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.