Pith. sign in

Paper Citation Record · LEDGER

A Framework for Uncertainty Quantification Based on Nearest Neighbors Across Layers

As of 9 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2506.19895.

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

pith.paper-citation-record.v1
2506.19895 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:10:54.328606Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

20 of 20 outbound references displayed

  • verified exact5
  • verified fuzzy0
  • unresolved14
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 916ef479-61a7-4507-89dc-a25bdf2bb622 · outbound

This paper cites Information Fusion76, 243–297 (2021).

A Framework for Uncertainty Quantification Based on Nearest Neighbors Across Layers Information Fusion76, 243–297 (2021)

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-06T23:10:54.229115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:10:54.229115Z digest=sha256:16db7049dedd90fc4667cb224d20665031f15ad46ea4e9f99e35687a366fefff

Observation a00ffe02-5db7-4eed-9d91-d1d2c6a031b8 · outbound

This paper cites Heliyon 4(11), e00938 (2018).https://doi.org/10.1016/j.heliyon.2018.e00938.

A Framework for Uncertainty Quantification Based on Nearest Neighbors Across Layers Heliyon 4(11), e00938 (2018).https://doi.org/10.1016/j.heliyon.2018.e00938

Reference 2

Resolution
verified exact
doi, observed 2026-08-06T23:10:54.565894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:10:54.234670Z digest=sha256:81c81ee76747d66eb9b6d49b5450598fbe31d383fe74c50fd4c4a3812f41d627

Observation 14d5c4a4-5a04-4b66-ae45-7e67adc2f32d · outbound

This paper cites Uncertainty Estimation Using a Single Deep Deterministic Neural Network.

A Framework for Uncertainty Quantification Based on Nearest Neighbors Across Layers Uncertainty Estimation Using a Single Deep Deterministic Neural Network

Reference 3

Resolution
verified exact
local_arxiv, observed 2026-08-06T23:10:54.550060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:10:54.239459Z digest=sha256:e1efb5da4e9135c614613ccaaa518ae45f50df1da2fbfb454b93a701ab6e1cb4

Observation f214675d-e849-4c41-9518-71058b76b2b9 · outbound

This paper cites IEEE Signal Processing Magazine29(6), 141–142 (2012).https://doi.

A Framework for Uncertainty Quantification Based on Nearest Neighbors Across Layers IEEE Signal Processing Magazine29(6), 141–142 (2012).https://doi

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T23:10:54.245369Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:10:54.245369Z digest=sha256:5e089a16ff1442f92f32b94093ba6b2799027f532a203f7cdd1f095b2a03551b

Observation 3fa10f2a-70d0-4dc6-b770-b254b38cf012 · outbound

This paper cites Pattern Recognition35(10), 2279–2301 (2002).https://doi.

A Framework for Uncertainty Quantification Based on Nearest Neighbors Across Layers Pattern Recognition35(10), 2279–2301 (2002).https://doi

Reference 5

Resolution
verified exact
doi, observed 2026-08-06T23:10:54.528432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:10:54.251135Z digest=sha256:ad3ab2dafda8ddd4a548fa56d397678a15b6461eb14cbe01e43d0a3eca39b7ec

Observation edfc05ca-f11d-44ed-bd80-9292830b51d2 · outbound

This paper cites Pattern Recognition Letters27(8), 861–874 (2006).

A Framework for Uncertainty Quantification Based on Nearest Neighbors Across Layers Pattern Recognition Letters27(8), 861–874 (2006)

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T23:10:54.256407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:10:54.256407Z digest=sha256:0a338e3de24c04b0cabf5ecfd8331d5ab70d34a3d38b3a8c7f26198b18635b27

Observation 359cca78-54bf-4267-a630-b34ee3868bf1 · outbound

This paper cites Artificial Intelligence Review 56(1), 1513–1589 (2023).https://doi.org/10.1007/s10462-023-10562-9.

A Framework for Uncertainty Quantification Based on Nearest Neighbors Across Layers Artificial Intelligence Review 56(1), 1513–1589 (2023).https://doi.org/10.1007/s10462-023-10562-9

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-06T23:10:54.261773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:10:54.261773Z digest=sha256:2a90e7f0c6fabee94e9f726dcf39d58d04eccf96002865b51337c9b72c864c8d

Observation 325f9592-6130-48ec-92a9-6c5dbea4e5e1 · outbound

This paper cites A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks.

A Framework for Uncertainty Quantification Based on Nearest Neighbors Across Layers A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T23:10:54.266760Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:10:54.266760Z digest=sha256:0538fdea6ea87fa3e41f097d1cf5355dcb7ae5a22fd901f7baa1dd3f9ea08229

Observation 1f426f4f-3cc1-46d8-9469-b09d64d7e0d7 · outbound

This paper cites Applied Soft Computing 149, 111027 (2023).https://doi.org/10.1016/j.asoc.2023.111027.

A Framework for Uncertainty Quantification Based on Nearest Neighbors Across Layers Applied Soft Computing 149, 111027 (2023).https://doi.org/10.1016/j.asoc.2023.111027

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-06T23:10:54.272401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:10:54.272401Z digest=sha256:c86b0f2fa0441438ef16a18a0175a5103840ce6f371ff5d164cbdb11f03a87a0

Observation e962baa6-2f4c-4a8b-832b-cd6d36e9eadb · outbound

This paper cites What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?.

A Framework for Uncertainty Quantification Based on Nearest Neighbors Across Layers What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T23:10:54.277292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:10:54.277292Z digest=sha256:82fae2475d363b774224d16af8ecdfcfef2662a2a554ad8bc6931aa4ca1d20fa

Observation 12bbdfa0-62db-41e9-8b37-a0c92964dbc0 · outbound

This paper cites https://doi.org/10.1016/j.strusafe.2008.06.

A Framework for Uncertainty Quantification Based on Nearest Neighbors Across Layers https://doi.org/10.1016/j.strusafe.2008.06

Reference 11

Resolution
verified exact
doi, observed 2026-08-06T23:10:54.466477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:10:54.282392Z digest=sha256:dbc76a6c0d1c06490419a55b985964d442a7672ade2960a315a2a87b28f3956a

Observation cc8eff81-2243-4611-8434-06d16a7102a8 · outbound

This paper cites an unresolved cited work.

A Framework for Uncertainty Quantification Based on Nearest Neighbors Across Layers Unresolved cited work

Reference 12

Resolution
unresolved
raw_fallback, observed 2026-08-06T23:10:54.894172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:10:54.287791Z digest=sha256:2ead7e086e8c6f14a2b5607a5edc4aa9ef4d4880a25cda67868fe0db734a7006

Observation d7410889-4048-4fb9-a0bc-9daf869171c6 · outbound

This paper cites A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks.

A Framework for Uncertainty Quantification Based on Nearest Neighbors Across Layers A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T23:10:54.292816Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:10:54.292816Z digest=sha256:069508d1e41993db96ca2374ea5d0cb3e6d06e412b9e8fd4bcf6001c452cb2c2

Observation 631931f4-38c2-429d-999d-84f140039c17 · outbound

This paper cites Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks.

A Framework for Uncertainty Quantification Based on Nearest Neighbors Across Layers Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T23:10:54.297850Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:10:54.297850Z digest=sha256:cfc7904ce064b06fc72b278ecbee51b23fc463383304bdc359464efdc0e940e8

Observation f12b9e6c-a4fe-4ca9-859e-98be316f2122 · outbound

This paper cites Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness.

A Framework for Uncertainty Quantification Based on Nearest Neighbors Across Layers Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T23:10:54.302495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:10:54.302495Z digest=sha256:75539677d2cf030419693eccb044b277eb1c2fe10e452e4246720553d602d961

Observation 248337dd-3256-46e5-b4f7-f84f06f96edf · outbound

This paper cites In: 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

A Framework for Uncertainty Quantification Based on Nearest Neighbors Across Layers In: 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-06T23:10:54.307969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:10:54.307969Z digest=sha256:273872fcd4d2ae5ba6079b2ee05087e7dca188581a58c796c40701f080acfbc9

Observation 2b68fbd4-b265-4769-a83a-53a3e8252459 · outbound

This paper cites an unresolved cited work.

A Framework for Uncertainty Quantification Based on Nearest Neighbors Across Layers Unresolved cited work

Reference 17

Resolution
verified exact
doi, observed 2026-08-06T23:10:54.407219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:10:54.313090Z digest=sha256:62847e741eeca1d11b582e60d6bcd66410f635f998936a001d899c8e76361324

Observation 403d6aeb-5382-4fea-ab29-d32ed9266ceb · outbound

This paper cites PloS one10, e0118432 (2015).

A Framework for Uncertainty Quantification Based on Nearest Neighbors Across Layers PloS one10, e0118432 (2015)

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-06T23:10:54.318599Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:10:54.318599Z digest=sha256:7836855ad0fcb39b92147193d6c8f5e29d3121a29e2a36f22033f3e005714ee6

Observation 7ac30172-7b5c-462e-abd6-2889a0e8253e · outbound

This paper cites npj Computational Materials9(1) (2023).

A Framework for Uncertainty Quantification Based on Nearest Neighbors Across Layers npj Computational Materials9(1) (2023)

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-06T23:10:54.323619Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:10:54.323619Z digest=sha256:d7a5efeddd8edb3471988b6b07049126857b97b2f1c1bca951bfe65ed51f4992

Observation ca6bd971-90df-4bcd-87a6-288d4127cccf · outbound

This paper cites Single Model Uncertainty Estimation via Stochastic Data Centering.

A Framework for Uncertainty Quantification Based on Nearest Neighbors Across Layers Single Model Uncertainty Estimation via Stochastic Data Centering

Reference 20

Resolution
metadata mismatch
local_arxiv, observed 2026-08-06T23:10:54.372517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T23:10:54.328606Z digest=sha256:5da548a2403959aa1c2d863e1e0d9f1faea6117d476bb715abfe01fd8cae8a40

Pith citing papers

No inbound Pith citation observations are available.