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Paper Citation Record · LEDGER

Universal randomised signatures for generative time series modelling

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2406.10214.

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

pith.paper-citation-record.v1
2406.10214 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 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T05:49:40.152316Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T07:26:45.973364Z

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 7465c833-fd37-46d2-a3a7-0c818707d554 · inbound

Signature Reconstruction from Randomized Signatures cites this paper.

Signature Reconstruction from Randomized Signatures Universal randomised signatures for generative time series modelling

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-09T05:49:40.152316Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T05:49:40.152316Z digest=sha256:ed82ee72ed83355fb0c1f99de40cdf42bd825a8d345b3c85bb9a7c22228c16da

Observation 87f31efb-8a13-45e4-96d7-9cb54c30a72d · inbound

Generating Financial Time Series by Matching Random Convolutional Features cites this paper.

Generating Financial Time Series by Matching Random Convolutional Features Universal randomised signatures for generative time series modelling

Reference 86

Resolution
verified exact
arxiv_id, observed 2026-07-02T07:26:45.974998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-28T06:56:06.376335Z digest=sha256:e324ef065548e25e58bfecce78162062bd4ee34b17ac8faaae9c02d630c6c0c7