Pith. sign in

Paper Citation Record · LEDGER

UniCL: A Universal Contrastive Learning Framework for Large Time Series Models

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2405.10597.

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

pith.paper-citation-record.v1
2405.10597 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 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:16:21.533167Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T04:28:53.434192Z

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 c7396559-9650-471f-8f66-02a1f346c736 · inbound

Universal Time-Series Representation Learning: A Survey cites this paper.

Universal Time-Series Representation Learning: A Survey UniCL: A Universal Contrastive Learning Framework for Large Time Series Models

Reference 113

Resolution
verified exact
arxiv_id, observed 2026-05-24T04:28:53.436768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-24T04:26:45.527625Z digest=sha256:f125cf2abe9a162de21d1eaba071d0fbfebf59d1d357cd7978f91f439ac064ad

Observation 847f3e85-3439-4821-853a-e1734036a08e · inbound

Decoupling Spatio-Temporal Prediction: When Lightweight Large Models Meet Adaptive Hypergraphs cites this paper.

Decoupling Spatio-Temporal Prediction: When Lightweight Large Models Meet Adaptive Hypergraphs UniCL: A Universal Contrastive Learning Framework for Large Time Series Models

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T14:16:21.533167Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:16:21.533167Z digest=sha256:89d697f70ae5f59941f82607fe8c6d6fffc7ded3024b8592bb683bd8a7c55d3d