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Paper Citation Record · LEDGER

Dimensionality compression and expansion in Deep Neural Networks

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:1906.00443.

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

pith.paper-citation-record.v1
1906.00443 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T21:49:05.467916Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T14:08:21.603819Z

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 2d7548dc-c47e-4fba-bbe3-a62046c54343 · inbound

Optimizing Latent Dimension Allocation in Hierarchical VAEs: Balancing Attenuation and Information Retention for OOD Detection cites this paper.

Optimizing Latent Dimension Allocation in Hierarchical VAEs: Balancing Attenuation and Information Retention for OOD Detection Dimensionality compression and expansion in Deep Neural Networks

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T04:42:37.758755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:42:37.758755Z digest=sha256:5079a232473f0aa9e57f5caf2fdc044f18913b23b4a2d1bd1801858c554709c7

Observation e150d8a7-1899-48ba-a430-82005e5b429a · inbound

Intermediate Representations are Strong AI-Generated Image Detectors cites this paper.

Intermediate Representations are Strong AI-Generated Image Detectors Dimensionality compression and expansion in Deep Neural Networks

Reference 46

Resolution
verified exact
arxiv_id, observed 2026-05-11T17:56:06.715675Z

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=2026-05-08T16:55:44.000342Z digest=sha256:a61c3e60526c3fc54fdc597b408cf6d1fc2ee0bf2cbf3bb928f12bdb479ef1b9

Observation 0206c378-2070-4e78-aa15-38a73e63a5b5 · inbound

The Stable Recovery Manifold: Geometric Principles Governing Recoverability in Continual Learning cites this paper.

The Stable Recovery Manifold: Geometric Principles Governing Recoverability in Continual Learning Dimensionality compression and expansion in Deep Neural Networks

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-07-03T14:08:21.605593Z

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=2026-06-27T07:15:03.905388Z digest=sha256:039e5a3c6e50961c35ad98cb1167e76eae499467af145b9033943773a793c458

Observation b223fd15-503e-48a4-a662-d3a995e29383 · inbound

Formalizing Latent Thoughts: Four Axioms of Thought Representation in LLMs cites this paper.

Formalizing Latent Thoughts: Four Axioms of Thought Representation in LLMs Dimensionality compression and expansion in Deep Neural Networks

Reference 63

Resolution
verified exact
arxiv_id, observed 2026-07-01T13:15:45.602112Z

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=2026-06-30T23:50:48.584391Z digest=sha256:ae6cc5fcd36bb949d93ff782171133283c19f783340dd93790ade490cf65e37d

Observation 4a91d622-0a59-4cd3-b96d-52925bb96075 · inbound

How to Tame Grokking: Representation Geometry as a Control Signal cites this paper.

How to Tame Grokking: Representation Geometry as a Control Signal Dimensionality compression and expansion in Deep Neural Networks

Reference 23

Resolution
unresolved
no resolver link, observed 2026-07-14T04:01:12.361370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T04:01:12.361370Z digest=sha256:ab0e58bc50f75e100f48b858962bfc51de1068090445d9f6adc8702232d93442

Observation d4ec326a-b65f-4eae-aba4-ff127f03c4ab · inbound

Complexity and Stability of Neural Activity Across Aging and Neurodegenerative Disease cites this paper.

Complexity and Stability of Neural Activity Across Aging and Neurodegenerative Disease Dimensionality compression and expansion in Deep Neural Networks

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T21:49:05.467916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T21:49:05.467916Z digest=sha256:ae52712307de3c7e3cb8ff22e201e4555055252e5e5be7c85a31ed99be207aaf