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Paper Citation Record · LEDGER

Is Epistemic Uncertainty Faithfully Represented by Evidential Deep Learning Methods?

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2402.09056.

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

pith.paper-citation-record.v1
2402.09056 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T01:02:15.461375Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T14:26:04.339772Z

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 1ebb8466-4b37-4c00-946a-67fdd65e19af · inbound

Provable Uncertainty Decomposition via Higher-Order Calibration cites this paper.

Provable Uncertainty Decomposition via Higher-Order Calibration Is Epistemic Uncertainty Faithfully Represented by Evidential Deep Learning Methods?

Reference 2678

Resolution
unresolved
no resolver link, observed 2026-08-11T04:37:21.695653Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:37:21.695653Z digest=sha256:6d71c143865bfd5b457a6e472ac5561459f489fe4c929b966370831345a78e16

Observation 8a5e1f35-a97f-4876-9cdf-08525384dabb · inbound

Uncertainty Quantification for Machine Learning in Healthcare: A Survey cites this paper.

Uncertainty Quantification for Machine Learning in Healthcare: A Survey Is Epistemic Uncertainty Faithfully Represented by Evidential Deep Learning Methods?

Reference 220

Resolution
unresolved
no resolver link, observed 2026-08-16T01:02:15.461375Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T01:02:15.461375Z digest=sha256:f4ddd035934210c98912e2f25f13d44ba759e3a11a664740eacce0c569d4c4d7

Observation c0c5ddd3-62b5-45e7-b474-817a7b2aa6db · inbound

Principled Input-Output-Conditioned Post-Hoc Uncertainty Estimation for Regression Networks cites this paper.

Principled Input-Output-Conditioned Post-Hoc Uncertainty Estimation for Regression Networks Is Epistemic Uncertainty Faithfully Represented by Evidential Deep Learning Methods?

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T12:01:36.208070Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:01:36.208070Z digest=sha256:ae8491bc53b8bdbfd1f6d8aca358aa3449cc54fceff9ea4f69b914beabd795a4

Observation 12f139ef-044a-429a-b2c6-7b965c2437f7 · inbound

Ensemble-Based Dirichlet Modeling for Predictive Uncertainty and Selective Classification cites this paper.

Ensemble-Based Dirichlet Modeling for Predictive Uncertainty and Selective Classification Is Epistemic Uncertainty Faithfully Represented by Evidential Deep Learning Methods?

Reference 13

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T00:15:51.997586Z

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=2026-05-10T18:38:30.129473Z digest=sha256:46a07af8c417ee6b36622d1baeaced8a640eca23030eb5ef5f24e3fa2b5e0ac4

Observation 72e3e072-986e-4c15-81ae-6b6436b030d6 · inbound

Do Not Imitate, Reinforce: Iterative Classification via Belief Refinement cites this paper.

Do Not Imitate, Reinforce: Iterative Classification via Belief Refinement Is Epistemic Uncertainty Faithfully Represented by Evidential Deep Learning Methods?

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-11T14:26:04.341693Z

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=2026-05-09T21:48:15.641442Z digest=sha256:0bfa799031f34de74ebaead20b2b316eb62db6499ee2df7e766afc57365b80fe