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Paper Citation Record · LEDGER

TimeSiam: A Pre-Training Framework for Siamese Time-Series Modeling

As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2402.02475.

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

pith.paper-citation-record.v1
2402.02475 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 2026-08-04T06:34:03.388597+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-09T01:38:50.523432Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-09T01:45:50.828562Z

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 dc6038d3-f274-4737-9cb2-06004ab614c7 · inbound

Deep Time Series Models: A Comprehensive Survey and Benchmark cites this paper.

Deep Time Series Models: A Comprehensive Survey and Benchmark TimeSiam: A Pre-Training Framework for Siamese Time-Series Modeling

Reference 196

Resolution
verified exact
arxiv_id, observed 2026-05-23T23:05:51.443981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-23T23:03:45.096751Z digest=sha256:22a651e0fa014a5c1871443bbc574f21c4faa0dd1ff970f755f2b62ad1396f7b

Observation c7f81548-5ab7-4872-b9a2-815f4c531d77 · inbound

Physical activities enable scalable foundation modelling for broad-spectrum health prediction cites this paper.

Physical activities enable scalable foundation modelling for broad-spectrum health prediction TimeSiam: A Pre-Training Framework for Siamese Time-Series Modeling

Reference 27

Resolution
verified exact
local_arxiv, observed 2026-07-09T01:45:50.829713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-07-09T01:38:50.523432Z digest=sha256:d8c0fd110a202ea8dc6ebd8ab3d0785c1420ed9b494956dfc543bd79733b367e