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Paper Citation Record · LEDGER

A statistical theory of cold posteriors in deep neural networks

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2008.05912.

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

pith.paper-citation-record.v1
2008.05912 v2

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 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:52:56.242887Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T20:40:08.509031Z

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 98763080-81ab-4a34-9f7e-ed17ac2864b2 · inbound

Are vision language models robust to uncertain inputs? cites this paper.

Are vision language models robust to uncertain inputs? A statistical theory of cold posteriors in deep neural networks

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-15T20:52:56.242887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:52:56.242887Z digest=sha256:198777df3366a2662fee22d33fe48156f270deae79deaf95542eb36210322f0a

Observation 6047bf42-f7e5-4b4a-8e58-ed85b56b8c67 · inbound

Gaussian Mean Field Variational Inference can Overestimate Predictive Variance cites this paper.

Gaussian Mean Field Variational Inference can Overestimate Predictive Variance A statistical theory of cold posteriors in deep neural networks

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-07-04T20:40:08.510492Z

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.

source=arxiv_source observed=2026-06-25T19:48:28.532570Z digest=sha256:9d30af3ffecddd0965ae38e390062ad0fda7d63d8a065a7daae02ca2d7b1b4a5