Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
SEGAN: semi-supervised learning approach for missing data imputation
As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2405.13089.
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 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-08T17:04:02.418499Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T17:51:08.003712Z
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 b6da89ef-bbae-4476-ad7d-a178a4efdf5d · inbound
Piper: Efficient Large-Scale MoE Training via Resource Modeling and Pipelined Hybrid Parallelism cites this paper.
Piper: Efficient Large-Scale MoE Training via Resource Modeling and Pipelined Hybrid Parallelism SEGAN: semi-supervised learning approach for missing data imputation
Reference 18
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T17:51:08.006379Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.