Paper Citation Record · LEDGER

Intrinsic dimension of data representations in deep neural networks

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:1905.12784.

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

pith.paper-citation-record.v1
1905.12784 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T13:42:54.685841Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T02:59:25.654173Z

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 f3a6c3e8-d498-4863-b474-6aff58fa3a9b · inbound

Phase Transitions in Large Language Models and the $O(N)$ Model cites this paper.

Phase Transitions in Large Language Models and the $O(N)$ Model Intrinsic dimension of data representations in deep neural networks

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T13:42:54.685841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 889cce7e-8fe9-4b41-a8c3-3eeb15bded7f · inbound

Redundancy, Isotropy, and Intrinsic Dimensionality of Prompt-based Text Embeddings cites this paper.

Redundancy, Isotropy, and Intrinsic Dimensionality of Prompt-based Text Embeddings Intrinsic dimension of data representations in deep neural networks

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T11:49:09.142320Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c6d5a7ad-77bb-4373-b981-53ab0f641779 · inbound

The Long Delay to Arithmetic Generalization: When Learned Representations Outrun Behavior cites this paper.

The Long Delay to Arithmetic Generalization: When Learned Representations Outrun Behavior Intrinsic dimension of data representations in deep neural networks

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-14T21:17:58.858987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d96b7da8-3fc6-4672-8db6-24183a846ddb · inbound

UR-JEPA: Uniform Rectifiability as a Regularizer for Joint-Embedding Predictive Architectures cites this paper.

UR-JEPA: Uniform Rectifiability as a Regularizer for Joint-Embedding Predictive Architectures Intrinsic dimension of data representations in deep neural networks

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-07-01T21:16:14.355230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 37cbf761-e6d7-48e3-a260-ce538491187e · inbound

The Geometry of Last-Layer Model Stealing cites this paper.

The Geometry of Last-Layer Model Stealing Intrinsic dimension of data representations in deep neural networks

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-07-02T16:27:09.533105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ea768161-99d3-4a66-8551-2954280102f8 · inbound

Patnaik-Pearson intrinsic dimension for internal representations of neural networks cites this paper.

Patnaik-Pearson intrinsic dimension for internal representations of neural networks Intrinsic dimension of data representations in deep neural networks

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T02:59:25.656471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2a3ba2ca-37a5-4cee-8ef3-47bcad18caa1 · inbound

Patnaik-Pearson intrinsic dimension for internal representations of neural networks cites this paper.

Patnaik-Pearson intrinsic dimension for internal representations of neural networks Intrinsic dimension of data representations in deep neural networks

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T23:49:02.146119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 23a8fef0-6aec-40e4-9c13-01f494ea5602 · inbound

Isotropy Cliffs: The Geometric Signature of Decision-Making in Large Language Models cites this paper.

Isotropy Cliffs: The Geometric Signature of Decision-Making in Large Language Models Intrinsic dimension of data representations in deep neural networks

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-05T00:16:15.164125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.