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Paper Citation Record · LEDGER

High-dimensional limit theorems for SGD: Effective dynamics and critical scaling

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2206.04030.

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

pith.paper-citation-record.v1
2206.04030 v4

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 2026-08-23T06:30:58.430688+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T19:04:55.474879Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T17:37:13.888777Z

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 d034a3f1-2925-49ba-8a10-c7acb69fba67 · inbound

Specialization of softmax attention heads: insights from the high-dimensional single-location model cites this paper.

Specialization of softmax attention heads: insights from the high-dimensional single-location model High-dimensional limit theorems for SGD: Effective dynamics and critical scaling

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-02T19:04:55.474879Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T19:04:55.474879Z digest=sha256:03f435c687bf209c0ac47a4b8cda410b8a845cc4ff7d37905327e61f52958de9

Observation 07ba7e8c-a0a1-49ca-a4e9-31bde8bdc47f · inbound

A Theory of Saddle Escape in Deep Nonlinear Networks cites this paper.

A Theory of Saddle Escape in Deep Nonlinear Networks High-dimensional limit theorems for SGD: Effective dynamics and critical scaling

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-11T16:51:05.743210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-09T14:54:47.763122Z digest=sha256:a140ff348390363e1886e2b1866f3e033cc80ada7006b2d0df837aa31e7eb70e

Observation 08425dca-1a0b-47b0-a45d-e0f474943da1 · inbound

A Theory of Saddle Escape in Deep Nonlinear Networks cites this paper.

A Theory of Saddle Escape in Deep Nonlinear Networks High-dimensional limit theorems for SGD: Effective dynamics and critical scaling

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-11T02:25:54.605129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-11T02:22:38.751375Z digest=sha256:b4b9ba4aa7573e4ddaee8404abbf97276287699bc0ef06fa88f96e35191ca71b

Observation 83d96471-f2e1-499c-99c7-5d843be7e41f · inbound

A Theory of Saddle Escape in Deep Nonlinear Networks cites this paper.

A Theory of Saddle Escape in Deep Nonlinear Networks High-dimensional limit theorems for SGD: Effective dynamics and critical scaling

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-07-01T00:45:12.072712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-07-01T00:37:16.364388Z digest=sha256:4742bed9dc664e4b6ed9ba4f7fbb8f7c06d2fb05ca8cfc7e04fb9fd2b4646b3b

Observation f5f0c226-becd-46ac-96a7-f71e226f106e · inbound

Homogenization of $\ell_2$-Adversarial Training in High-Dimensions: Exact Dynamics under Stochastic Gradient Descent cites this paper.

Homogenization of $\ell_2$-Adversarial Training in High-Dimensions: Exact Dynamics under Stochastic Gradient Descent High-dimensional limit theorems for SGD: Effective dynamics and critical scaling

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-07-02T17:37:13.890565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-07-02T17:31:02.850791Z digest=sha256:be841952124cfe64432ab72a36a6be1cb580f47234559894b81993feb838fcf4

Observation 30dc2c8d-f4f8-4a8e-960e-9d122c492f3f · inbound

Benign Overfitting Does Not Occur in Diffusion Models cites this paper.

Benign Overfitting Does Not Occur in Diffusion Models High-dimensional limit theorems for SGD: Effective dynamics and critical scaling

Reference 48

Resolution
unresolved
no resolver link, observed 2026-07-12T07:49:39.894643Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-12T07:49:39.894643Z digest=sha256:da894c0cec49652d28d793cf94bc41fa8601879733584ea35a1dc3c067078d86