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Paper Citation Record · LEDGER

Latent space configuration for improved generalization in supervised autoencoder neural networks

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2402.08441.

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

pith.paper-citation-record.v1
2402.08441 v3

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 2026-08-06T23:26:48.472632Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T22:53:23.448565Z

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 7f6f7758-c666-4248-b774-fd7e06d89286 · inbound

Imputation of Longitudinal Data Using GANs: Challenges and Implications for Classification cites this paper.

Imputation of Longitudinal Data Using GANs: Challenges and Implications for Classification Latent space configuration for improved generalization in supervised autoencoder neural networks

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-06T23:26:48.472632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:26:48.472632Z digest=sha256:31203396e4f1baa3bdf2f5f125098fd44960e47b7434a540d067f18d8a134a35

Observation d22d50e6-d3df-43fa-9587-9546e8eb5d20 · inbound

Using predefined vector systems to speed up neural network multimillion class classification cites this paper.

Using predefined vector systems to speed up neural network multimillion class classification Latent space configuration for improved generalization in supervised autoencoder neural networks

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-13T22:53:23.454754Z

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=2026-05-13T22:50:23.083429Z digest=sha256:a02c0c59a624fd3eb3f9b5ee64658ce95d346f425a7b646905bfa898b6b660d5