Paper Citation Record · LEDGER

Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2306.10125.

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

pith.paper-citation-record.v1
2306.10125 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:38:05.971679Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-25T07:25:29.483804Z

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 1487d8d7-a0f0-4e31-b4a2-fdcf5243686f · inbound

Time-LLM: Time Series Forecasting by Reprogramming Large Language Models cites this paper.

Time-LLM: Time Series Forecasting by Reprogramming Large Language Models Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects

Reference 123

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T16:03:17.103575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 75dd3231-8a7c-4fa8-b3ca-e231e50ab00b · inbound

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

Universal Time-Series Representation Learning: A Survey Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects

Reference 231

Resolution: verified exact; arxiv_id, observed 2026-05-24T04:28:53.329962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 4da67f5d-d746-4459-b1d2-d0b6cdd0313e · inbound

Information Subtraction: Learning Representations for Conditional Entropy cites this paper.

Information Subtraction: Learning Representations for Conditional Entropy Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-10T22:38:05.971679Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62b15337-1497-41d8-8985-299c7a68a804 · inbound

HyperIMTS: Hypergraph Neural Network for Irregular Multivariate Time Series Forecasting cites this paper.

HyperIMTS: Hypergraph Neural Network for Irregular Multivariate Time Series Forecasting Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-07T14:53:56.258120Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a4dd78f-7433-4c5f-bed7-48d23891bda8 · inbound

Next-Latent Prediction Transformers Learn Compact World Models cites this paper.

Next-Latent Prediction Transformers Learn Compact World Models Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-25T07:25:29.487033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e72676a6-393e-4744-9e0f-370e90fdfcdd · inbound

Next-Latent Prediction Transformers Learn Compact World Models cites this paper.

Next-Latent Prediction Transformers Learn Compact World Models Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-03T23:27:57.555716Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b82e2f55-f9c4-49ab-9826-482dd6bdd0b6 · inbound

Modular Foundation Models for Time-Series Perception in Digital Twins cites this paper.

Modular Foundation Models for Time-Series Perception in Digital Twins Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects

Reference 125

Resolution: unresolved; no resolver link, observed 2026-07-12T01:22:51.284207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.