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Paper Citation Record · LEDGER

Generative machine learning methods for multivariate ensemble post-processing

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2211.01345.

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

pith.paper-citation-record.v1
2211.01345 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 2026-08-21T06:32:19.484+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T23:19:48.265501Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T22:45:50.928336Z

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 66c4a6df-4a45-4cd7-9307-c11f4a63e4af · inbound

Modeling Spatial Extremal Dependence of Precipitation Using Distributional Neural Networks cites this paper.

Modeling Spatial Extremal Dependence of Precipitation Using Distributional Neural Networks Generative machine learning methods for multivariate ensemble post-processing

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-23T22:45:50.931079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-23T22:43:48.396816Z digest=sha256:a05984092c412bf6a73996a9210bf714b2705add6e214f3def97c01fc67c0b4b

Observation 3bdc4192-2f69-4cbe-b344-baa2860832cd · inbound

Towards Neural No-Resource Language Translation: A Comparative Evaluation of Approaches cites this paper.

Towards Neural No-Resource Language Translation: A Comparative Evaluation of Approaches Generative machine learning methods for multivariate ensemble post-processing

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-10T23:19:48.265501Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:19:48.265501Z digest=sha256:1517acaf9bb64b15ab3ac051c22f67e2e03b5046de2e22f3b8b256ef824c1f2e