Paper Citation Record · LEDGER

SGD and Weight Decay Secretly Minimize the Rank of Your Neural Network

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2206.05794.

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

pith.paper-citation-record.v1
2206.05794 v7

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T16:21:41.231938Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T16:07:09.448556Z

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 7219d340-2303-4817-a016-d38329641ca0 · inbound

On Generalization Bounds for Neural Networks with Low Rank Layers cites this paper.

On Generalization Bounds for Neural Networks with Low Rank Layers SGD and Weight Decay Secretly Minimize the Rank of Your Neural Network

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-12T16:21:41.231938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 706d7da5-4244-4ea5-aa3d-85df53b06cf3 · inbound

The Features at Convergence Theorem: a first-principles alternative to the Neural Feature Ansatz for how networks learn representations cites this paper.

The Features at Convergence Theorem: a first-principles alternative to the Neural Feature Ansatz for how networks learn representations SGD and Weight Decay Secretly Minimize the Rank of Your Neural Network

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T19:31:20.239832Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1fdfa8de-876d-4140-be48-13626623bd21 · inbound

Evolutionary Search for Automated Design of Uncertainty Quantification Methods cites this paper.

Evolutionary Search for Automated Design of Uncertainty Quantification Methods SGD and Weight Decay Secretly Minimize the Rank of Your Neural Network

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-13T19:18:09.217340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a0e1c6e9-3caf-40c9-ad18-a3986cf9d05a · inbound

Does Weight Decay Enhance Training Stability? cites this paper.

Does Weight Decay Enhance Training Stability? SGD and Weight Decay Secretly Minimize the Rank of Your Neural Network

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-20T19:53:42.998253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 99b448d0-bb6a-4de8-9beb-de8a7e182b88 · inbound

Weight Decay Regimes in Grokking Transformers: Cheap Online Diagnostics cites this paper.

Weight Decay Regimes in Grokking Transformers: Cheap Online Diagnostics SGD and Weight Decay Secretly Minimize the Rank of Your Neural Network

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-21T07:34:02.899180Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ec9025ee-74ed-47e5-9d30-0ac4460eb6e1 · inbound

The Implicit Bias of Depth: From Neural Collapse to Softmax Codes cites this paper.

The Implicit Bias of Depth: From Neural Collapse to Softmax Codes SGD and Weight Decay Secretly Minimize the Rank of Your Neural Network

Reference 137

Resolution: verified exact; arxiv_id, observed 2026-05-25T05:26:38.933941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8a2839c8-1691-49ff-8d3e-24e1994385e0 · inbound

Deciphering Two Training Clocks in Grokking via Deep Linear Network Theory with Conditional ReLU Reduction cites this paper.

Deciphering Two Training Clocks in Grokking via Deep Linear Network Theory with Conditional ReLU Reduction SGD and Weight Decay Secretly Minimize the Rank of Your Neural Network

Reference 25

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T12:06:56.089444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f3c56663-8160-484e-8fb3-f7c1313bdbc8 · inbound

Reversible Foundations: Training a 120B Sparse MoE through State-Preserving Scaling cites this paper.

Reversible Foundations: Training a 120B Sparse MoE through State-Preserving Scaling SGD and Weight Decay Secretly Minimize the Rank of Your Neural Network

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-07-02T16:07:09.450255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.