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Paper Citation Record · LEDGER

High dimensional analysis reveals conservative sharpening and a stochastic edge of stability

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2404.19261.

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

pith.paper-citation-record.v1
2404.19261 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:48:49.116497Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T15:59:56.364296Z

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 d210d09d-bd03-4756-84ab-8877e7587d6b · inbound

Scaling Collapse Reveals Universal Dynamics in Compute-Optimally Trained Neural Networks cites this paper.

Scaling Collapse Reveals Universal Dynamics in Compute-Optimally Trained Neural Networks High dimensional analysis reveals conservative sharpening and a stochastic edge of stability

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-06T20:48:49.116497Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:48:49.116497Z digest=sha256:d99839946759c1d1a22f982fb0d652660dc54db2aff46dad83661c3901f842e3

Observation f7212db3-57d9-442c-9bcb-7aad474c666a · inbound

Large Spikes in Stochastic Gradient Descent: A Large-Deviations View cites this paper.

Large Spikes in Stochastic Gradient Descent: A Large-Deviations View High dimensional analysis reveals conservative sharpening and a stochastic edge of stability

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-15T13:30:51.087424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-15T13:30:04.366752Z digest=sha256:15aeb90138a8c4342e89ca394d131a74ea217b0288cb29ba1006663813f45d4c

Observation 9b253682-df68-46ee-8891-15db789df791 · inbound

Momentum Further Constrains Sharpness at the Edge of Stochastic Stability cites this paper.

Momentum Further Constrains Sharpness at the Edge of Stochastic Stability High dimensional analysis reveals conservative sharpening and a stochastic edge of stability

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-10T13:20:26.339993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-10T13:12:58.210967Z digest=sha256:d220d102527c484cc13ed3df7ca1b4c18a7bd82ffd445d412344e523aca8d40e

Observation 7388fe7e-3989-4d31-8354-d91033008540 · inbound

A Fast-Convergence Resolution of the Stochastic Eigenproblem Using Halley's Method and the Spectral-Chaos Approach cites this paper.

A Fast-Convergence Resolution of the Stochastic Eigenproblem Using Halley's Method and the Spectral-Chaos Approach High dimensional analysis reveals conservative sharpening and a stochastic edge of stability

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-07-04T15:59:56.366021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-26T01:12:55.503098Z digest=sha256:1db6052688afece73377295e0420ef7efe530664cda616f03d09f3f9b67025bc

Observation 7428a34f-4b0e-4694-9dce-baadea88429d · inbound

The Map Behind the Flow: Finite-Step Gradient Descent as a Dynamical System cites this paper.

The Map Behind the Flow: Finite-Step Gradient Descent as a Dynamical System High dimensional analysis reveals conservative sharpening and a stochastic edge of stability

Reference 39

Resolution
unresolved
no resolver link, observed 2026-07-11T10:24:00.719150Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-11T10:24:00.719150Z digest=sha256:d80959734f2ed00e1b38951a5bb6c521fa794b6408d1f04787f0bf5e2e8b2919