Pith. sign in

Paper Citation Record · LEDGER

Learning Curves for SGD on Structured Features

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2106.02713.

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

pith.paper-citation-record.v1
2106.02713 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:39:56.630377Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T17:20:00.898403Z

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 59f46074-dd84-4d79-b353-30f07fd49667 · inbound

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression cites this paper.

Scaling Law for Stochastic Gradient Descent in Quadratically Parameterized Linear Regression Learning Curves for SGD on Structured Features

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T22:45:01.729201Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T22:45:01.729201Z digest=sha256:12d777d2295eb7e6041d01d86152d73dc8cfc5bce5b5a2cc36bac7d2efd19d1c

Observation 55134020-6bd9-4488-883d-1951954437b1 · inbound

Corner Gradient Descent cites this paper.

Corner Gradient Descent Learning Curves for SGD on Structured Features

Reference 1970

Resolution
unresolved
no resolver link, observed 2026-08-16T12:39:56.630377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:39:56.630377Z digest=sha256:2183fddb62d19c107e6b764b9bd8f8ab6797bdaaedd2dd976ff91bd46f180320

Observation 2498633a-4663-42ca-a32f-4e50f8f85f2b · inbound

A Simplified Analysis of SGD for Linear Regression with Weight Averaging cites this paper.

A Simplified Analysis of SGD for Linear Regression with Weight Averaging Learning Curves for SGD on Structured Features

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-15T19:41:05.269216Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:41:05.269216Z digest=sha256:8f221028c1dd340dcf297b616bc34e878a6aa6361da6cb3bf58c364962270a69

Observation 1b7d1605-e725-40b2-b661-06cc2c980cc8 · inbound

Seesaw: Accelerating Training by Balancing Learning Rate and Batch Size Scheduling cites this paper.

Seesaw: Accelerating Training by Balancing Learning Rate and Batch Size Scheduling Learning Curves for SGD on Structured Features

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-04T09:38:49.434717Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T09:38:49.434717Z digest=sha256:bc9f86b6b170db162ba0f9480c851e1961ec6c30fe6ff19fb6b615139ba3f1db

Observation 3b9dbe4f-b7ce-4801-8a1d-f7da7a486998 · inbound

Unifying Learning Dynamics and Generalization in Transformers Scaling Law cites this paper.

Unifying Learning Dynamics and Generalization in Transformers Scaling Law Learning Curves for SGD on Structured Features

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-03T14:02:56.646373Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T14:02:56.646373Z digest=sha256:7a89d192020c3428423e7b2c675b35d8ffd1d986b23ffa8ece73deb705120ee8

Observation d21ae77e-42af-46f9-bea5-6a0da67e67fc · inbound

Universal One-third Time Scaling in Learning Peaked Distributions cites this paper.

Universal One-third Time Scaling in Learning Peaked Distributions Learning Curves for SGD on Structured Features

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-03T05:01:10.761729Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T05:01:10.761729Z digest=sha256:00f2cebf8857e528cc0ca3facdbe4c10ae423cd696ff3074804c9cacda92371d

Observation 8d100ea2-4755-4cbe-870f-fb928b46f84e · inbound

Neural Scaling Universality: If Exponents Are Fixed, Time to Understand Coefficients cites this paper.

Neural Scaling Universality: If Exponents Are Fixed, Time to Understand Coefficients Learning Curves for SGD on Structured Features

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-07-04T17:20:00.900196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-06-25T23:45:54.283436Z digest=sha256:85dc8be6b72f3e40b1acd389ac7df6f507c0a9f0e11ce27ac105f9eaea4b53c2

Observation f41e988c-b174-4943-9c22-ed9ac2c4e491 · 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 Learning Curves for SGD on Structured Features

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-07-02T17:37:13.853798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-07-02T17:31:02.850791Z digest=sha256:6f38ad53d0568f8227f62d95bf376f8db9c900561d752e6055b350c4063c8ddb

Observation 6656265a-06a3-4261-89db-376489d3b9f2 · inbound

A Defense of the Quadratic Model cites this paper.

A Defense of the Quadratic Model Learning Curves for SGD on Structured Features

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-01T06:58:09.845006Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T06:58:09.845006Z digest=sha256:ab8a73552ae7d5f8bcbdde56b4d893ceb02dcb5e76ff772f172012bb74beb933