Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Why Not to Use Zero Imputation? Correcting Sparsity Bias in Training Neural Networks
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:1906.00150.
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 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-28T11:10:52.856825Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T02:06:27.687011Z
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 92d98ead-cd03-41f0-9123-241d968527b9 · inbound
AugMask: Training Diffusion Models on Incomplete Tabular Data via Stochastic Augmentation and Masking cites this paper.
AugMask: Training Diffusion Models on Incomplete Tabular Data via Stochastic Augmentation and Masking Why Not to Use Zero Imputation? Correcting Sparsity Bias in Training Neural Networks
Reference 4
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T02:06:27.688784Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.