Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Statistical and Algorithmic Insights for Semi-supervised Learning with Self-training
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2006.11006.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T15:32:15.371424Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-21T05:13:58.173979Z
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 66bd5ed1-f4d6-466d-818f-5bc84cd59f6e · inbound
Self-Boost via Optimal Retraining: An Analysis via Approximate Message Passing cites this paper.
Self-Boost via Optimal Retraining: An Analysis via Approximate Message Passing Statistical and Algorithmic Insights for Semi-supervised Learning with Self-training
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:32:15.371424Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5b1cfb36-3c8b-4145-9a9c-48a554c42068 · inbound
Self-Distillation is Optimal Among Spectral Shrinkage Estimators in Spiked Covariance Models cites this paper.
Self-Distillation is Optimal Among Spectral Shrinkage Estimators in Spiked Covariance Models Statistical and Algorithmic Insights for Semi-supervised Learning with Self-training
Reference 64
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T01:07:54.799743Z
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.
Observation 7955d99b-5f60-4be3-b84e-2130e1914dc2 · inbound
VBFDD-Agent for Electric Vehicle Battery Fault Detection and Diagnosis: Descriptive Text Modeling of Battery Digital Signals cites this paper.
VBFDD-Agent for Electric Vehicle Battery Fault Detection and Diagnosis: Descriptive Text Modeling of Battery Digital Signals Statistical and Algorithmic Insights for Semi-supervised Learning with Self-training
Reference 38
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T05:13:58.176227Z
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.