Pith. sign in

Paper Citation Record · LEDGER

Why are Big Data Matrices Approximately Low Rank?

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1705.07474.

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

pith.paper-citation-record.v1
1705.07474 v2

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 2026-08-07T12:27:46.656377Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

8
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation a399c26f-aaff-4f3e-ac5c-dfcfc11cffc8 · inbound

Impact of Bottleneck Layers and Skip Connections on the Generalization of Linear Denoising Autoencoders cites this paper.

Impact of Bottleneck Layers and Skip Connections on the Generalization of Linear Denoising Autoencoders Why are Big Data Matrices Approximately Low Rank?

Reference 2018

Resolution
unresolved
no resolver link, observed 2026-08-07T12:27:46.656377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:27:46.656377Z digest=sha256:3ac912e1c9eac653b154cfa8b5dbefa9baabe1215b80e782c8721e358efe3347

Observation db775097-22a3-4f96-836c-888dfbe3be6e · inbound

Unlearning with Asymmetric Sources: Improved Unlearning-Utility Trade-off with Public Data cites this paper.

Unlearning with Asymmetric Sources: Improved Unlearning-Utility Trade-off with Public Data Why are Big Data Matrices Approximately Low Rank?

Reference 48

Resolution
verified exact
arxiv_id, observed 2026-07-04T22:48:26.405768Z

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=arxiv_source observed=2026-05-13T05:56:38.042978Z digest=sha256:e6043839ef5ea018b95fcaeaaa7dd219ac847e2d37b36d88f64511485e8619f3