Paper Citation Record · LEDGER

Overfitted high-dimensional matrix factorizations via adaptive spectral shrinkage

As of 14 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 0 inbound Pith citation observations for arXiv:2606.19540.

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

pith.paper-citation-record.v1
2606.19540 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-26T19:32:24.426617Z

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

12 of 12 outbound references displayed

verified exact3
verified fuzzy0
unresolved8
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 695e5584-96a1-423c-9f8a-618b9a760c06 · outbound

This paper cites Simpler Proofs for Approximate Factor Models of Large Dimensions.

Overfitted high-dimensional matrix factorizations via adaptive spectral shrinkage Simpler Proofs for Approximate Factor Models of Large Dimensions

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-07-04T02:39:24.942090Z

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.

Observation a2fd79a6-553c-40b4-b4f6-1cfc16eb3b9c · outbound

This paper cites & Cho, H.

Overfitted high-dimensional matrix factorizations via adaptive spectral shrinkage & Cho, H

Reference 2

Resolution: unresolved; no resolver link, observed 2026-06-26T19:32:24.426617Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9973838f-82bc-4224-9053-55e693850d24 · outbound

This paper cites Blessing of dimension in Bayesian inference on covariance matrices.

Overfitted high-dimensional matrix factorizations via adaptive spectral shrinkage Blessing of dimension in Bayesian inference on covariance matrices

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-08-10T02:08:53.155123Z

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.

Observation 5e032d9f-2e09-42ea-ac02-b938308fb6c7 · outbound

This paper cites & Jakubzick, C.

Overfitted high-dimensional matrix factorizations via adaptive spectral shrinkage & Jakubzick, C

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-26T19:32:24.426617Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0e92f68-fb9d-4361-9a17-d42633f1d710 · outbound

This paper cites Overfitted high-dimensional matrix fac- torizations via adaptive spectral shrinkage.

Overfitted high-dimensional matrix factorizations via adaptive spectral shrinkage Overfitted high-dimensional matrix fac- torizations via adaptive spectral shrinkage

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-07-04T02:39:24.946962Z

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.

Observation a085f766-6180-4f47-81dd-2535974329c9 · outbound

This paper cites We proceed by showing consistency for the residual error variance.

Overfitted high-dimensional matrix factorizations via adaptive spectral shrinkage We proceed by showing consistency for the residual error variance

Reference 6

Resolution: unresolved; no resolver link, observed 2026-06-26T19:32:24.426617Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 02607f61-d157-41e3-9729-f11bd3ff1d2a · outbound

This paper cites Then, with probability at least 1−𝑜(1), || ˜𝑍|| 2 ≲𝜌 2 𝑝||Ψ −1 𝑛, 𝑗 ||max 𝑗=1,..., 𝑝 𝜎2 𝑗 ≲ 𝑝 𝑛 ≍1, since||Ψ −1 𝑛,𝑙 || ≍ 1 𝑛, and, by Lemma 8, || ˆΛ||≲ √𝑝≍ √𝑛.

Overfitted high-dimensional matrix factorizations via adaptive spectral shrinkage Then, with probability at least 1−𝑜(1), || ˜𝑍|| 2 ≲𝜌 2 𝑝||Ψ −1 𝑛, 𝑗 ||max 𝑗=1,..., 𝑝 𝜎2 𝑗 ≲ 𝑝 𝑛 ≍1, since||Ψ −1 𝑛,𝑙 || ≍ 1 𝑛, and, by Lemma 8, || ˆΛ||≲ √𝑝≍ √𝑛

Reference 7

Resolution: unresolved; no resolver link, observed 2026-06-26T19:32:24.426617Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62e0fb82-527d-4aec-9b77-3da64fd267c1 · outbound

This paper cites an unresolved cited work.

Overfitted high-dimensional matrix factorizations via adaptive spectral shrinkage Unresolved cited work

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-26T19:32:24.426617Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23a3695e-4664-4994-ba91-8c897b325655 · outbound

This paper cites Then, with probability at least1−𝑜(1), we have √𝑛−𝐶 √ 𝑘≤𝑠 𝑙 (𝐹) ≤ √𝑛+𝐶 √ 𝑘,(𝑙=1,.

Overfitted high-dimensional matrix factorizations via adaptive spectral shrinkage Then, with probability at least1−𝑜(1), we have √𝑛−𝐶 √ 𝑘≤𝑠 𝑙 (𝐹) ≤ √𝑛+𝐶 √ 𝑘,(𝑙=1,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-26T19:32:24.426617Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7c4b6970-1c95-4ae0-80b9-dd5e96f257ab · outbound

This paper cites Let𝑀Λ ⊤ 0 =𝑈 0,1:𝑘 𝐷0,1:𝑘 𝑉 ⊤ 0,1:𝑘 be the singular value decomposition of the signal matrix, with𝑈 0 ∈R 𝑛×𝑘 having orthonormal columns.

Overfitted high-dimensional matrix factorizations via adaptive spectral shrinkage Let𝑀Λ ⊤ 0 =𝑈 0,1:𝑘 𝐷0,1:𝑘 𝑉 ⊤ 0,1:𝑘 be the singular value decomposition of the signal matrix, with𝑈 0 ∈R 𝑛×𝑘 having orthonormal columns

Reference 10

Resolution: unresolved; no resolver link, observed 2026-06-26T19:32:24.426617Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 512e36b0-55a7-407f-b531-597afdfa4617 · outbound

This paper cites Lemma 8.Suppose Assumption 1–4 hold and𝐻=O (𝑛 2/5).

Overfitted high-dimensional matrix factorizations via adaptive spectral shrinkage Lemma 8.Suppose Assumption 1–4 hold and𝐻=O (𝑛 2/5)

Reference 11

Resolution: malformed identifier; no resolver link, observed 2026-06-26T19:32:24.426617Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d938ad0b-4ce5-45a1-84c8-7f83cdf324d9 · outbound

This paper cites 29 Lemma 12.Let𝛿 2 𝑗 = 𝑣𝑠 2+| |𝑦 (𝑗) − ˆ𝑀 ˆ𝜆𝑗 | |2 𝑣+𝑛.

Overfitted high-dimensional matrix factorizations via adaptive spectral shrinkage 29 Lemma 12.Let𝛿 2 𝑗 = 𝑣𝑠 2+| |𝑦 (𝑗) − ˆ𝑀 ˆ𝜆𝑗 | |2 𝑣+𝑛

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-26T19:32:24.426617Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.