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Paper Citation Record · LEDGER

On Last-Layer Algorithms for Classification: Decoupling Representation from Uncertainty Estimation

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2001.08049.

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

pith.paper-citation-record.v1
2001.08049 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:49:36.822802Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

18
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 0b3b1346-474d-4a1a-8af3-75b64c81a4f7 · inbound

B-PL-PINN: Stabilizing PINN Training with Bayesian Pseudo Labeling cites this paper.

B-PL-PINN: Stabilizing PINN Training with Bayesian Pseudo Labeling On Last-Layer Algorithms for Classification: Decoupling Representation from Uncertainty Estimation

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-06T20:49:36.822802Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:49:36.822802Z digest=sha256:c6d0b14d496f15711865cd26c8718c92c8c0577e62a774f63041768f540240ed

Observation 0334abdd-c1d2-4377-a131-536e7ca40e7b · inbound

Uncertainty quantification for trustworthy deep learning: Methods and measures cites this paper.

Uncertainty quantification for trustworthy deep learning: Methods and measures On Last-Layer Algorithms for Classification: Decoupling Representation from Uncertainty Estimation

Reference 2020

Resolution
verified exact
local_arxiv, observed 2026-07-31T13:25:51.915791Z

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=2026-07-31T13:23:56.753478Z digest=sha256:5d1174955bde97ea0cab727e299a097252792762b8c48cb1657532546e697dbd